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*The competition host prepares the data and a description of the problem *Participants experiment with different techniques and compete against each other to produce the best models. *Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas.
Kaggle, a subsidiary of Google LLC, is an online community of data scientists and machine learning practitioners. Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges. (Source: Wikipedia)
Business organisations can improve decision making by using kaggle as it *Identify a valuable machine learning problem that you have the data for. *Work with us to refine the problem statement and finalize the dataset. *Collaborate with us as we build out your competition's pages.
Kaggle, a subsidiary of Google, it is an online community of data scientists and machine learning practitioners. Kaggle got its start in 2010 by offering machine learning competitions. Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. The competition host prepares the data and a description of the problem. Participants experiment with different techniques and compete against each other to produce the best models. Work is shared publicly throughKaggle Kernels to achieve a better benchmark and to inspire new ideas.
Steps to use kaggle : step 1: pick the programme language. Step 2 : load, navigate and plot the data. Step 3 : Training a model. Step 4 : tackle the getting started competition. Step 5: complete to maximize learning not earning.
2GZ19MBA46 Vijay ganji Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems
Kaggle is a software which helps in productive business decision making: 1) Kaggle provides immense computational power through their servers. By using their site, you get access to state of the art machine learning and data analysis packages, pre-installed without compatibility issues. 2) The company also creates incentives for collaboration, and has fostered an open and welcoming community that encourages helping each other to produce better algorithms and results which also helps in mutual problem solving. 3) Kaggle is also becoming a repository of vast, clean, and easy to work with datasets. This makes the company get a huge information access through the vast datasets.
Pooja Halkarni Roll no. 33 B div 2GZ19MBA11 Businesses are organizational bodies that frame economic activity. Control the inner workings of things like finance, product sales, HR, and customer happiness so to make it better and more productive businesses use cookies on Kaggle to deliver their services, understand web traffic, in short Kagle is mostly used for better coustmer satisfaction and improving experience on the site.
Pooja Halkarni Roll no. 33 B div 2GZ19MBA11 Businesses are organizational bodies that frame economic activity. Control the inner workings of things like finance, product sales, HR, and customer happiness so to make it better and more productive businesses use cookies on Kaggle to deliver their services, understand web traffic, in short Kagle is mostly used for better coustmer satisfaction and improving experience on the site.
Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges. What is kaggle used for? Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems.
Kaggle makes it easy to connect your data with data scientists.
Kaggle is a platform for data science competitions. kaggle help you solve difficult problems, recruit strong teams, and amplify the power of your data science talent.
- Kaggle you’ll find all the code & data you need to do your data science work. Use over 19,000 public datasets and 200,000 public notebooks to conquer any analysis in no time.
-Kaggle provides immense computational power through their servers. By using their site, you get access to state of the art machine learning and data analysis packages, pre-installed without compatibility issues.
-The company also creates incentives for collaboration, and has fostered an open and welcoming community that encourages helping each other to produce better algorithms and results.
-The increasingly symbiotic relationship between companies that need machine learning expertise, and data science competition platform kaggle has greatly impacted how rapid advancement is being achieved.
-This relationship has also changed the hiring landscape. Companies today face ever-increasing pressure to innovate in order to remain competitive, and they are pursuing comparatively unconventional means for discovering and attracting new talent in order to maintain their edge.
-The need for machine learning talent is so great, that companies are looking far further afield than once they might have.
-Kaggle is becoming a repository of vast, clean, and easy to work with datasets.
Kaggle products are kaggle kerne, kaggle datasets,kaggle learn and jobs board.The type is subsidiary it is about data science.
Kaggleis a subsidiary of Google is an online community of data scientists and machine learning practitioners. It allows users to find and publish data sets,explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
The importance of the data lies in consistency and continual growth. It enables companies to create new business opportunities and generate more revenues and produce actionable insights. They even make or break the decisions of the company.
Mitali Nevagi USN: 2GI19MBA53 Kaggle is subsidiary of Google LLC, is an online community of data science and machine learning practitioners allowes users to find and publish data seta, explore and build modela in a web based data science environment, works with other data scientists and machine learning engineering and enter competitions to solve data science challenges. Business organizations can improve decision making with the help of kaggle. As follows;
It identify a valuable machine learning problem that you have the data for. It work with them to refine the problem statement and finalize the dataset. It is very powerful tool for AI and Machine learning developers that has been growing exponentially today. It receive code and docs from the winners, and follow up with knowledge transfer calls. Hence kaggle is a very important and essential tool of Google for business organizations which makes complicated work very easier.
Services provided by Kaggle:- 1.Machine learning competitions: this was Kaggle's first product. Companies post problems and machine learners compete to build the best algorithm.
2.Kaggle Kernels: a cloud-based workbench for data science and machine learning. Allows data scientists to share code and analysis in Python and R. Over 150K "kernels" (code snippets) have been shared on Kaggle covering everything from sentiment analysis to object detection.
3.Public datasets platform: community members share datasets with each other. Has datasets on everything from bone x-rays to results from boxing bouts.
4.Jobs board: employers post machine learning and AI jobs.
Kaggle is a global platform which hosts competitions, datasets, kernels and discussions regarding data science and machine learning.
People from all over the world can use kaggle may it be, developers, researchers, engineers, etc. Here they share data or information related to data science and machine learning which helps the community to learn data science machine learning.
If you do really good at this machine learning and data science top companies hire and will also be awarded with handsome salary. Through kaggle companies get to know a lot of skilled candidates and come in contact with them and may hire them too. Which will help their organisation perform better.
Kaggle is an Online platform to find and publish data sets, work with other data scientists & enter into competitions to solve various problems around the globe. Kaggle was founded by Anthony Goldbloom and Ben Hammer in April 2010.
Business Organizations can improve their Decision Making using Kaggle because, 1) Kaggle provides Machine Learning Competitions. Here, Companies post their problems and machine learners compete to build the best algorithm and solutions. These competitions have resulted in the successful projects like HIV Research, etc.
2) A person will be competing with the best data scientists in the world. It brings out the best from each individual.
3) Kaggle is under a time limit. It forces us to be time efficient and reaches time management.
Kaggle is a software that helps in business for productive decision making 1) It offers data sets to the organisation from which they can infer and analyse the data which will in turn assist the organisation to come to a decision 2) It can also be called as a collaborative platform for companies, researchers, statisticians and data miners who utilize produce and analyse the data
Omkar, How kaggle help the decision making. Say for example there is delhi rainfall data. The competition model may help delhi government to take care natural calamities
Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges. What is kaggle used for? Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems.
✓Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. ✓You can compete on many problems. ✓The competition host prepares the data and a description of the problem. ✓Participants experiment with different techniques and compete against each other to produce the best models. ✓Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas.
Mitigating risk and fraud. Kaggle can be used to identify data that stands out in some way. They create statistical, network, path, and big data methodologies for predictive fraud propensity models and use those to create alerts that help ensure timely responses when unusual data is recognized.
Delivering relevant products. Kaggle can be used in organizations to find when and where their products sell best. This can help deliver the right products at the right time—and can help companies develop new products to meet their customers’ needs.
Personalized customer experiences. One of the benefit of kaggle could be the ability for sales and marketing teams to understand their audience on a very granular level. With this knowledge, an organization can create the best possible customer experiences.
The process of data munging and pre/post-processing used in Kaggle competitions are steps. There might be other similarities here and there, but they do not overshadow the three core differences in objectives, techniques, and data gathering.
1. What types of questions can data science answer? “Data science and statistics are not magic. ... Step 1: Define the problem. First, it's necessary to accurately define the data problem that is to be solved. ... Step 2: Decide on an approach. ... Step 3: Collect data. ... Step 4: Analyze data. ... Step 5: Interpret results. ... Conclusion.
Mitigating risk and fraud. Kaggle can be used to identify data that stands out in some way. They create statistical, network, path, and big data methodologies for predictive fraud propensity models and use those to create alerts that help ensure timely responses when unusual data is recognized.
Delivering relevant products. Kaggle can be used in organizations to find when and where their products sell best. This can help deliver the right products at the right time—and can help companies develop new products to meet their customers’ needs.
Personalized customer experiences. One of the benefit of kaggle could be the ability for sales and marketing teams to understand their audience on a very granular level. With this knowledge, an organization can create the best possible customer experiences.
Kaggle one of the largest data science and which to find data using various tools for decesion making.Kaggle allows users to find data sets and build various models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges. Kaggle provides various opportunities using their site people can access for machine learning programs and data analysis.Kaggle helps easy to work with large of data sets and helps company for better decesion making.
Kaggle, the Google acquired data Science platform, started as a virtual meeting point for machine learning geeks to compete on predictive accuracy scores. Despite being a free service, Kaggle can help address an increasing number of data challenges : 1) how to find reliable data sources to enrich existing customer and marketing data 2) how to find ideas, inspiration and relevant code for a new data analysis without reinventing the wheel 3) how to collaborate efficiently on a data project with colleagues 4) how to apply machine learning and artificial intelligence to marketing analytics projects.
Hence, basically their goal is to leverage the collective intelligence of thousands of data scientists around the world to solve a data problem.
Nikhila Rattu USN:2GZ19MBA01 Kaggle supports a variety of dataset publication formats, it strongly encourage dataset publishers to share their data in an accessible, non-proprietary format if possible. The accessible data formats are better supported on the platform, they are also easier to work with for more people regardless of their tools.This helps us to learn why and how to make less well supported file types as accessible as possible to the data science community.
Kaggle, the Google acquired data Science platform, started as a virtual meeting point for machine learning geeks to compete on predictive accuracy scores. Despite being a free service, Kaggle can help address an increasing number of data challenges : 1) how to find reliable data sources to enrich existing customer and marketing data 2) how to find ideas, inspiration and relevant code for a new data analysis without reinventing the wheel 3) how to collaborate efficiently on a data project with colleagues 4) how to apply machine learning and artificial intelligence to marketing analytics projects.
Hence, basically their goal is to leverage the collective intelligence of thousands of data scientists around the world to solve a data problem.
I✓dentify a valuable machine learning problem that you have the data for. ✓You can compete on many problems. ✓The competition host prepares the data and a description of the problem. ✓Participants experiment with different techniques and compete against each other to produce the best models. ✓Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas.
1.Participants experiment with different techniques and compete against each other to produce the best models. Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas. Submissions can be made through Kaggle Kernels, through manual upload or using the Kaggle API. For most competitions, submissions are scored immediately (based on their predictive accuracy relative to a hidden solution file) and summarized on a live leaderboard.
2.The competition host prepares the data and a description of the problem.
3. After the deadline passes, the competition host pays the prize money in exchange for "a worldwide, perpetual, irrevocable and royalty-free license to use the winning Entry", i.e. the algorithm, software and related intellectual propertydeveloped, which is "non-exclusive unless otherwise specified".
Kaggle a platform for data science competitions,can be intimidating for beginners to get into. Top team boast decades of combined experience,tackling ambitious problems such as to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers. Various features to be handled 1. These are usually sponsored by companiwc, organisations,or even government.They have largest prize pool. 2. These are research orientated and have little to no prize money. They also have non traditional submission processes. 3. These are sponsored by companies who want to hire data scientists. These are still relatively uncommon.
Kaggle also helps : 1. Each competition is self contaunco you don't need to scope your own project or collect data,which helps you to focus on other skills. 2. The best way to learn data science is by doing as long as you don't stress out about winning every problem you can still practice interesting problems. 3. discussion and winner interviews are enlightened each competition has it's own discussion board and debriefs with the winners. You can peek into the thought proccess of more experienced data scientists.
1.Kaggle got its start in 2010 by offering machine learning competitions.
2.Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
3.Kaggle allows users to find and publish data sets, explore and build models in a web-based dat, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
4.Kaggle's first product Companies post problems and machine learners compete to build the best algorithm.
Divya V Palankar USN-2GI19MBA025 Kaggle is an online community of data scientist and machine learning practitioners. Kaggle got start in 2010 by offering machine learning competition and now also offers a public data plat form, cloud based workbench of data science and artificial intelligence education. Participants experiment with different techniques and compet against each other to produce the best models. Work is shared publicly through kaggle kernels to achieve a better benchmark and to inspire new ideas Several academics papers have been published on the basis of finding made in kaggle competition. A key to this is effect of the leaderboard which encourages to participants to continue innovating beyond existing best practices.
SRIKUMAR PATIL USN:2GZ19MBA43 Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems. The importance of the data lies in consistency and continual growth. It enables companies to create new business opportunities and generate more revenues and produce actionable insights.They even make or break the decisions of the company.
sharvari agnihotri Roll no 44 division - b kaggle is a website that hosts machine learning competitions.Along with competitions it also hosts following three important things: 1 Data sets : Even the ones not related to any competition it houses 9500+ data sets as compared to 300 competitions at a time of writing.So you can sharpen your skills with whatever dats sets amuses or interests you.
2 kernels: They are just kaggle' s version of Jupyter notebooks which I turn are really effective and cool way of sharing code along with lots of visualisations and outputs.
3 learn: This tab contains free practical hand on courses that cover the minimum prerequisites needed to quickly get started in the field.
How do they help organisations in Decsion making? - Enterprises today have access to various kinds of data from the touchpoint of customers including websites,business apps,social media pages, blogs,etc. However, just gathering the data is not enough for positive impact on business. There is need to analyse and collate data into pieces of value added information. It is used in following ways for decision making by organisations: • Improve customer engagement retention: As the data from various sources is collected from customer touchpoint it can be analysed further and Decisions can be made about what exactly are the customers demanding and their requirements. Companies have been using real time data to one to one personalized services.
•Enhance operational efficiency: Today companies are leveraging data to automate processes optimize effienciency of their businesses.For example, Tesla's are embedded with sensors that collect data and send it to the central servers for analysis.
• Increased capacity without extra investment: Telecommunication companies uses big data analytics to reduce network errors,optimise resources and improving customer experience with the real time data.
This Merk European drug company has improved their formulations using Kaggle competition is as follows: 1. It is a machine learning engineer and has helped Merk a European company to improve its technology as per latest trends in market so that day to day transactions are been recorded.
2. Here through Kaggle work is shared publicly and help us to achieve benchmark in the market. and help them to solve the problems.
3. Kaggle helps this company to have a data science environment in their company so that they can easily access the drugs all over the world.
Kaggle helps connect recruiters and candidates through their Job board. The company also creates incentives for collaboration, and has fostered an open and welcoming community that encourages helping each other to produce better algorithms and results which also helps in mutual problem solving. Kaggle is also becoming a repository of vast, clean, and easy to work with datasets. This makes the company get a huge information access through the vast datasets.
mindset that techniques, objectives, and processes prioritized in Kaggle competitions reflect those in a typical business environment. Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems The biggest challenge with this mindset is that there are core fundamental differences between Data Science used in Kaggle competitions and that practiced in an industry setting (what I call Industry Data Science). I will go into three specific reasons why this is the case, and how we can set the right expectations for those who are transitioning into the field.
Kaggle allowing anyone to get their hands on real-world data and giving them the opportunity to solve hard machine learning challenges .so using the real world dada the decision making and forecasting becomes easy and even kaggle provides immense cputational power through their servers which is very helpfulKaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems.
Kaggle is platform to complete with others in competition which are based on machine learning tasks.you may know about codechef ,Hackerrank etc..so kaggle is also like them,but the key difference is the competition are only related to machine learning,data science,deep learning or AI related.
• The competition host prepares the data and a description of the problem. • Participants experiment with different techniques and compete against each other to produce the best models. • Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas.
Kaggle is a very popular platform that’s great for aspiring Data Scientists to pick up skills on applied Machine Learning: preprocessing, pipelining, algorithm optimization. Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
Sir it uses decision tree model. The rain data is distributed according to the area, location, average rain fall, previous years rainfall and then compares such parameters with the present data.
Kaggle started in the 2010 by offering machine learning competitions and now also offers a public data platform, a cloud-based workbench for data science, and Artificial Intelligence education. Kaggel is a platform for predictive modeling and analytics compitition in which companies and researchers post data miners compete to produce the best models for predicting and describing the data.
Shreya sainuche 2GZ19MBA34 Kaggle got its start in 2010 offering machine learning competitions and now aslo offers a public data platform. A cloud based workbench for data science and artificial intelligence education.kaggle has run hundreds of machine learning competitors.competitons have resulted in many successful projects including furthering the state of the art in HIV research,chess ratings and traffic forecasting.
Kaggle is platform to compete with others in competitions which are based on machine learning tasks. You may know about Codechef, Hackerrank etc., so kaggle is also like them, but the key difference is the competition are only related to machine learning, data science, Deep learning or AI related.Well using Kaggle is really good thing for learning some trends and techniques in machine learning or data science. If you are really good in data science then I would suggest you to take part in competition. You will find dozens of them on Kaggle. If you are not really good in data science then you should use Kaggle for learning purpose. You can read blogs, interviews of grand masters and winners of different competitions. You can read articles related to some techniques in data science. And when you get comfortable with data science then go to competition section and take part in competition. Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
2GZ19MBA50 *Kaggle is a online platform which hosts machine learning and data science competitions which helps organisation solve their real life problems. Kaggle holds half a million data scientists on its platform.
*Once an organization has made its data available via Kaggle Prospect, members of the Kaggle community can submit suggestions and analyses about how the data can be used (“data prospecting”). Kaggle can tailor the results of this data prospecting to match the client’s desire, whether it be developing predictive modeling problems or creating a data visualization
*Kaggle’s community of nearly 40,000 data scientists will comment and discuss the data set in a collaborative forum. The Kaggle community at large can vote for the ideas and suggestions they expect to draw the most value out of the data, and a panel of judges from the client organization will analyze the top ideas and select a winner. When data prospecting results in a well-posed predictive modeling question, the organization can choose to run a competition on Kaggle immediately.
1) kaggle provide reliable data to the organisation while decision making. 2) kaggle is more valuable than prediction. 3) kaggle helps in building the trust in your decision.
1)The competition host prepares the data and a description of the problem.
2)Participants experiment with different techniques and compete against each other to produce the best models. Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas. Submissions can be made through Kaggle Kernels, through manual upload or using the Kaggle API. For most competitions, submissions are scored immediately (based on their predictive accuracy relative to a hidden solution file) and summarised on a live leaderboard.
3)After the deadline passes, the competition host pays the prize money in exchange for "a worldwide, perpetual, irrevocable and royalty-free license to use the winning Entry", i.e. the algorithm, software and related intellectual property developed, which is "non-exclusive unless otherwise specified".
Business Description 1)Organization is engaged in providing computer peripherals, parts, memory cards, clinical instrument, medical lab items and clinical softwares. Main Income is from products and services.
2)Company is engaged in providing Revenue Cycle Management, tax management, IT sotware services, and finance and accounting BPO. Main Income is from pharma companies billing and revenue, finance services.
3)The organization is engaged in R&D projects to licensed technologies for the Group's businesses in collaboration with its technology, production, environment setup and marketing divisions(engineering, life sciences and material sciences). Main income is from retainership fees and manufacturing unit setups.
4)Company is engaged in providing security surveillance, detective services and research areas. Mian income is from security deveoped products and R&D services.
The benefits of Kaggle are: 1. Can publish high quality data set. 2. Can get you Feedback directly through forums from different experts 3. Free data science and machine learning courses. 4. Making use of Data from famous companies and non profit organizations 5. Usage of all types of data such as customer data,log files, timeseries, html pages, images and documents
The examples of machine learning competitions which help organization make decisions using kaggle database : 1.Predicting compound toxicity given its molecular structure 2. Automatically grading student written essays 3. Personalizing web search results 4. Detecting diabetic retinopathy
The importance of the data lies in consistency and continual growth. It enables companies to create new business opportunities and generate more revenues and produce actionable insights. They even make or break the decisions of the company. Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems.
Akshata halagannavar USN: 2GI19MBA08 Roll no. 4 (A div)
Inside Kaggle you’ll find all the code & data you need to do your data science work. Use over 19,000 publicdatasets and 200,000 publicnotebooks to conquer any analysis in no time.
Kaggle’s model is based on presenting machine learning competitions that function as opportunities for machine learning enthusiasts to test out, and further develop, their skills. From a learning perspective, this makes a great deal of sense, and the elements of play and competition add layers of motivation and excitement. The real key to Kaggle’s success, however, is that these competitions rely on real-world data provided by real-world companies.
The increasingly symbiotic relationship between companies that need machine learning expertise, and data science competition platforms like Kaggle, has greatly impacted how rapid advancement is being achieved. This relationship has also changed the hiring landscape. Companies today face ever-increasing pressure to innovate in order to remain competitive, and they are pursuing comparatively unconventional means for discovering and attracting new talent in order to maintain their edge. The need for machine learning talent is so great, that companies are looking far further afield than once they might have.
Vishal kurade 2GZ19MBA53 Kaggle’s model is based on presenting machine learning competitions that function as opportunities for machine learning enthusiasts to test out, and further develop, their skills. Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.kaggle provides platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
Kaagle helps in providing variety of data publication format. It helps us to start data science projects, and also allows us to find and publish high quality data set, hence it aslo help us in building Codes and Models.
Kaagle provide a data set referring to which the organisation can take various decission.
1.It is an online learning aap where we can Choose any course and buit our skills.
2.if here we can try learning different techniques and compete with other participants by producing best and innovative models.
3.it helps in machine and artificial intelligence learning.
4.Kaagle provides opportunities to the people in web based data science environment.
5.Kaagle provides an option where participants can share their work publically which sets a benchmark to inspire new and innovative ideas
Kaggle also supports special BigQuery Datasets. BigQuery is a “big data” SQL store invented by Google. Many massive public datasets, like all the code in GitHub and the complete history of the Bitcoin blockchain, are available publically through the Google BigQuery Public Datasets initiative. Some of these are in turn also available as Kaggle Datasets!
Kaggle, an online community for data scientists and a platform for data science competitions, has unveiled a new and timely bounty-paying challenge: the Covid-19 Open Research Dataset Challenge, or CORD-19.
CORD-19 asks artificial intelligence (AI) and machine learning researchers to develop text and data mining tools to analyse a dataset comprising tens of thousands of articles on virology and infectious disease. The goal is to help provide answers for 10 tasks, or lines of inquiry about the disease.
The prize for each of the tasks in the CORD-19 challenge is $1000, delivered as cash or as a charitable donation to research and relief efforts.
The world isn’t lacking for research about Covid-19. Kaggle’s dataset contains “over 29,000 scholarly articles, including over 13,000 with full text, about Covid-19, SARS-CoV-2, and related coronaviruses,” according to the challenge introduction.
But there’s little time to paw manually through those haystacks of research for the needles we need, so Kaggle is encouraging the use of machine learning techniques like natural language processing to get relevant data into the right hands more quickly.
1) kaggle provide reliable data to the organisation while decision making. 2) kaggle is more valuable than prediction. 3) kaggle helps in building the trust in your decision.
Kaggle is an online community of data scientists and machine learning practitioners. It allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers. Machine learning was Kaggle's first product. Companies post problems and machine learners compete to build the best algorithm. It has resulted in many successful projects including furthering the state of the art in HIV research, chess ratings and traffic forecasting.
Kaggle is a base to compete with others in competition which are mainly based on machine learning tasks.In this kaggle competition are only based on machine learning and data science. Using kaggle helps for learning some trends and techniques in machine learning. You can also take kaggle for learning of machine learning and data science.
How it helps to business organisation ? 1 As a kaggle is a base for machine learning and data science, it connects companies facing hard problems with data scientists who can solve them. 2 participants experiments the given problems with different technique and compete against each other to get best result. 3 The competitions often comes with money price, job opportunity and also it helps to learn new participants to learn. In this kaggle. 4 Kaggle enables tha data scientists and other developers to engage in running machine learning contests, write and share code and to host datasets. 5 There are currently over one million kaggle members. And this data community has submitted above 4 million learning models. 6 We can get interesting and challenging projects where the participants van practice.
*Kaggle is a platform for doing and sharing. *It's all about google platform which host the competition, datasets, discussion regarding machine learning in different area's.
Business organization can improve there decision by using kaggle *Where organization can do lot of data science and machine learning without heating up there systems. *The organization can publish high quality datasets on kaggle. * Kaggle has greatly impacted how rapid advancement is being achieved. *Kaggle is a really great distribution platform for innovative techniques. *The benefits of being active on Kaggle are not just limited to the rich set of problems available, and the support from the community.
Kaggle got its start in 2010 by offering machine learning competitions and now also offers a public data platform, a cloud-based workbench for data science, and Artificial Intelligence education. Its key personnel were Anthony Goldbloom and Jeremy Howard. Nicholas Gruen was founding chair succeeded by Max Levchin. Equity was raised in 2011 valuing the company at $25 million. On 8 March 2017, Google announced that they were acquiring
Personalized customer experiences. One of the benefit of kaggle could be the ability for sales and marketing teams to understand their audience on a very granular level. With this knowledge, an organization can create the best possible customer experiences.
Jyoti bhadaganvi USN 2GI19MBA36 (A) Kaggle helps business organizations to take effective decisions the following are reasons how it will improve the organization decisions. 1.it provides description of the problem and helps to take different techniques to produce best models. 2.understand and analyze the business problems. 3.machine learning competition company can post the problem to build best algorithm. 4. Its helps to develop software and intellectual property development.
Kaggle is a platform for predictive modelling analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. and
You can use it in following ways:
1. Competitions | Kaggle
You can compete on many problems. Find the
problems you find interesting and compete to provide better solution to the problem.
2. Datasets Kaggle The best place to discover and seamlessly analyze open data. You can find any dataset of your interest and apply analytical methods to fine tune your analytical capabilities.
3. Kernels Kaggle Allows, user to share and learn from different approaches.
Rahul Patil USN- 2GZ19MBA22 Kaggle’s model is based on presenting machine learning competitions that function as opportunities for machine learning enthusiasts to test out, and further develop, their skills. From a learning perspective, this makes a great deal of sense, and the elements of play and competition add layers of motivation and excitement. The real key to Kaggle’s success, however, is that these competitions rely on real-world data provided by real-world companies. The importance of the data lies in consistency and continual growth. It enables companies to create new business opportunities and generate more revenues and produce actionable insights.They even make or break the decisions of the company.
Kaggle helps organization in many ways to help in decision making and some of them are as follows :
1) Kaggle helps in handling massive file sizes also for sampling and extracting useful subsets of data 2) Kaggle leaderboard ranking is immediate feedback on how well you have broken down and solved the problem
Raghotam chimmalagi Usn 2GZ19MBA21 (A) The importance of the data lies in consistency and continual growth. It enables companies to create new business opportunities and generate more revenues and produce actionable insights. They even make or break the decisions of the company.
Kaggle is a platform to compete with others in competition which are based on machine learning tasks. Where the machine learning algorithms are used and desion tree ,apriori algorithms are used for the decision making fir the business units
Kaggle is the perfect platform to learn from other data scientist all over the world and share your knowledge. This platform grown to become the largest data science community in the world. Kaggle contributors, who had the opportunity to work in a team , teamt also benefits kaggles by exposing them two different tools and techniques helpful in solving data problems
Soumya Gouranna 2GZ19MBA41 Companies use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. Kaggle, a popular platform for data science competitions, can be intimidating for beginners to get into. Kaggle competitions encourage you to squeeze out every last drop of performance, while typical data science encourages efficiency and maximizing business impact.
Kaggle has a cool feature in which participants can submit "kernels," which are short scripts that explore a concept, showcase a technique, or even share a solution.
Kaggle is a very popular platform that’s great for aspiring Data Scientists to pick up skills on applied Machine Learning: preprocessing, pipelining, algorithm optimization.
Kagglers often rely on complicated, multi-layered ML and Deep Learning approach for the competition. Specifically, they use stacking/blending, as it remains the most successful strategy for winning Kaggle competitions. Erin LeDell, the Chief Decision Scientist at H2O.ai, lays out this point in one of her seminars.
Name:Mumtaz Naik USN:2GI19MBA54 Roll No.:24(A) 1)A Kaggle is a gaggle of data scientists. 2)Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. We can compete on many problems. 3)The competition host prepares the data and a description of the problem. Participants experiment with different techniques and compete against each other to produce the best models. Work is shared publicly through Kaggle Kernels. 4)We can read articles related to some techniques in data science. And when we get comfortable with data science then go to competition section and take part in competition. 5)Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
1. Kaggle exposes you to a wide range of machine learning problems such as forecasting, sentiment analysis, natural language processing, image recognition, etc. This motivates you to learn as much as you can about the problem domain, the type of data involved, and the various algorithms which may be applicable. 2. Kaggle is under a time limit. This 'forces' you to work in a very efficient manner in developing and testing out alternative ideas quickly. 3. Kaggle helps in learning the value of cross-validation. Re-sampling and retraining your model multiple times to validate that your solution is working and not over-fitting the data. 4. Kaggle competitions force you to code and recode your solution in most resource efficient manner possible. All these features of kaggle helps in better decision making process.
It's all about google platform which host the competition, datasets, discussion regarding machine learning in different area's.Kaggle helps business organizations to take effective decisions Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.As a kaggle is a base for machine learning and data science, it connects companies facing hard problems with data scientists who can solve them.
Anup Yankati Roll no 06 2GI19MBA12 Kaggle helps connect recruiters and candidates through their Job board. The company also creates incentives for collaboration, and has fostered an open and welcoming community that encourages helping each other to produce better algorithms and results which also helps in mutual problem solving. Kaggle is also becoming a repository of vast, clean, and easy to work with datasets. This makes the company get a huge information access through the vast datasets.
103 comments:
Nagaratna K
Roll no 59
2GI19MBA55
*The competition host prepares the data and a description of the problem
*Participants experiment with different techniques and compete against each other to produce the best models.
*Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas.
You can find huge databases of the world
Kaggle, a subsidiary of Google LLC, is an online community of data scientists and machine learning practitioners. Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
(Source: Wikipedia)
Ok Sir
Business organisations can improve decision making by using kaggle as it
*Identify a valuable machine learning problem that you have the data for.
*Work with us to refine the problem statement and finalize the dataset.
*Collaborate with us as we build out your competition's pages.
Merk a Europian drug company improved their formulations using kaggle competition winner models
Please write your name and USN
Ok sir
2GZ19MBA21
Kaggle, a subsidiary of Google, it is an online community of data scientists and machine learning practitioners. Kaggle got its start in 2010 by offering machine learning competitions.
Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
The competition host prepares the data and a description of the problem. Participants experiment with different techniques and compete against each other to produce the best models. Work is shared publicly throughKaggle Kernels to achieve a better benchmark and to inspire new ideas.
Steps to use kaggle :
step 1: pick the programme language.
Step 2 : load, navigate and plot the data.
Step 3 : Training a model.
Step 4 : tackle the getting started competition.
Step 5: complete to maximize learning not earning.
2GZ19MBA46 Vijay ganji
Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems
Kaggle is a software which helps in productive business decision making:
1) Kaggle provides immense computational power through their servers. By using their site, you get access to state of the art machine learning and data analysis packages, pre-installed without compatibility issues.
2) The company also creates incentives for collaboration, and has fostered an open and welcoming community that encourages helping each other to produce better algorithms and results which also helps in mutual problem solving.
3) Kaggle is also becoming a repository of vast, clean, and easy to work with datasets. This makes the company get a huge information access through the vast datasets.
Good
Pooja Halkarni
Roll no. 33 B div
2GZ19MBA11
Businesses are organizational bodies that frame economic activity. Control the inner workings of things like finance, product sales, HR, and customer happiness so to make it better and more productive businesses use cookies on Kaggle to deliver their services, understand web traffic, in short Kagle is mostly used for better coustmer satisfaction and improving experience on the site.
Pooja Halkarni
Roll no. 33 B div
2GZ19MBA11
Businesses are organizational bodies that frame economic activity. Control the inner workings of things like finance, product sales, HR, and customer happiness so to make it better and more productive businesses use cookies on Kaggle to deliver their services, understand web traffic, in short Kagle is mostly used for better coustmer satisfaction and improving experience on the site.
Absolutely right
Correct
I think you searched different for this discussion. We are discussing on kaggle from google
Gurunath V. Shiroorkar
2GI19MBA31
Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
What is kaggle used for?
Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems.
AKASH .PATIL
2GI19MBA06
DIV 'A'
Kaggle makes it easy to connect your data with data scientists.
Kaggle is a platform for data science competitions.
kaggle help you solve difficult problems, recruit strong teams, and amplify the power of your data science talent.
- Kaggle you’ll find all the code & data you need to do your data science work. Use over 19,000 public datasets and 200,000 public notebooks to conquer any analysis in no time.
-Kaggle provides immense computational power through their servers. By using their site, you get access to state of the art machine learning and data analysis packages, pre-installed without compatibility issues.
-The company also creates incentives for collaboration, and has fostered an open and welcoming community that encourages helping each other to produce better algorithms and results.
-The increasingly symbiotic relationship between companies that need machine learning expertise, and data science competition platform kaggle has greatly impacted how rapid advancement is being achieved.
-This relationship has also changed the hiring landscape. Companies today face ever-increasing pressure to innovate in order to remain competitive, and they are pursuing comparatively unconventional means for discovering and attracting new talent in order to maintain their edge.
-The need for machine learning talent is so great, that companies are looking far further afield than once they might have.
-Kaggle is becoming a repository of vast, clean, and easy to work with datasets.
To be precise, you can find online shopping intention result on kaggle data sets. The firm like bigbasket can use that data
Kaggle products are kaggle kerne, kaggle datasets,kaggle learn and jobs board.The type is subsidiary it is about data science.
Kaggleis a subsidiary of Google is an online community of data scientists and machine learning practitioners. It allows users to find and publish data sets,explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
Omkar Patil
Roll no 29
Usn 2GZ19MBA06
The importance of the data lies in consistency and continual growth. It enables companies to create new business opportunities and generate more revenues and produce actionable insights.
They even make or break the decisions of the company.
Mitali Nevagi USN: 2GI19MBA53
Kaggle is subsidiary of Google LLC, is an online community of data science and machine learning practitioners allowes users to find and publish data seta, explore and build modela in a web based data science environment, works with other data scientists and machine learning engineering and enter competitions to solve data science challenges.
Business organizations can improve decision making with the help of kaggle. As follows;
It identify a valuable machine learning problem that you have the data for.
It work with them to refine the problem statement and finalize the dataset.
It is very powerful tool for AI and Machine learning developers that has been growing exponentially today.
It receive code and docs from the winners, and follow up with knowledge transfer calls.
Hence kaggle is a very important and essential tool of Google for business organizations which makes complicated work very easier.
Services provided by Kaggle:-
1.Machine learning competitions: this was Kaggle's first product. Companies post problems and machine learners compete to build the best algorithm.
2.Kaggle Kernels: a cloud-based workbench for data science and machine learning. Allows data scientists to share code and analysis in Python and R. Over 150K "kernels" (code snippets) have been shared on Kaggle covering everything from sentiment analysis to object detection.
3.Public datasets platform: community members share datasets with each other. Has datasets on everything from bone x-rays to results from boxing bouts.
4.Jobs board: employers post machine learning and AI jobs.
Manashi Patil
2GI19MBA48
"B"division
Roll no:- 21
Shriya Chiniwalar
2GZ19MBA35
Kaggle is a global platform which hosts competitions, datasets, kernels and discussions regarding data science and machine learning.
People from all over the world can use kaggle may it be, developers, researchers, engineers, etc.
Here they share data or information related to data science and machine learning which helps the community to learn data science machine learning.
If you do really good at this machine learning and data science top companies hire and will also be awarded with handsome salary.
Through kaggle companies get to know a lot of skilled candidates and come in contact with them and may hire them too. Which will help their organisation perform better.
Kaggle is an Online platform to find and publish data sets, work with other data scientists & enter into competitions to solve various problems around the globe.
Kaggle was founded by Anthony Goldbloom and Ben Hammer in April 2010.
Business Organizations can improve their Decision Making using Kaggle because,
1) Kaggle provides Machine Learning Competitions. Here, Companies post their problems and machine learners compete to build the best algorithm and solutions. These competitions have resulted in the successful projects like HIV Research, etc.
2) A person will be competing with the best data scientists in the world. It brings out the best from each individual.
3) Kaggle is under a time limit. It forces us to be time efficient and reaches time management.
Priyanka Mahindrakar
USN: 2GZ19MBA20
Kaggle is a software that helps in business for productive decision making
1) It offers data sets to the organisation from which they can infer and analyse the data which will in turn assist the organisation to come to a decision
2) It can also be called as a collaborative platform for companies, researchers, statisticians and data miners who utilize produce and analyse the data
Omkar, How kaggle help the decision making. Say for example there is delhi rainfall data. The competition model may help delhi government to take care natural calamities
OMKAR HAWALDAR
ROLL NO 28 DIV: A
2GZ19MBA05
Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
What is kaggle used for?
Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems.
✓Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
✓You can compete on many problems.
✓The competition host prepares the data and a description of the problem. ✓Participants experiment with different techniques and compete against each other to produce the best models.
✓Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas.
Srushti kalburgi
USN- 2GZ19MBA43
Roll no. 51
Mitigating risk and fraud. Kaggle can be used to identify data that stands out in some way. They create statistical, network, path, and big data methodologies for predictive fraud propensity models and use those to create alerts that help ensure timely responses when unusual data is recognized.
Delivering relevant products. Kaggle can be used in organizations to find when and where their products sell best. This can help deliver the right products at the right time—and can help companies develop new products to meet their customers’ needs.
Personalized customer experiences. One of the benefit of kaggle could be the ability for sales and marketing teams to understand their audience on a very granular level. With this knowledge, an organization can create the best possible customer experiences.
Vishal Kagati
2GZ19MBA52
Div-B Roll no. 55
The process of data munging and pre/post-processing used in Kaggle competitions are steps. There might be other similarities here and there, but they do not overshadow the three core differences in objectives, techniques, and data gathering.
Excellent
Pooja Koliwad
Roll no 32
USN 2GZ19MBA12
1. What types of questions can data science answer? “Data science and statistics are not magic. ...
Step 1: Define the problem. First, it's necessary to accurately define the data problem that is to be solved. ...
Step 2: Decide on an approach. ...
Step 3: Collect data. ...
Step 4: Analyze data. ...
Step 5: Interpret results. ...
Conclusion.
Ok Sir
Srushti kalburgi
USN- 2GZ19MBA43
Roll no. 51
Mitigating risk and fraud. Kaggle can be used to identify data that stands out in some way. They create statistical, network, path, and big data methodologies for predictive fraud propensity models and use those to create alerts that help ensure timely responses when unusual data is recognized.
Delivering relevant products. Kaggle can be used in organizations to find when and where their products sell best. This can help deliver the right products at the right time—and can help companies develop new products to meet their customers’ needs.
Personalized customer experiences. One of the benefit of kaggle could be the ability for sales and marketing teams to understand their audience on a very granular level. With this knowledge, an organization can create the best possible customer experiences.
Shubham Hande 2GI19MBA32
Kaggle one of the largest data science and which to find data using various tools for decesion making.Kaggle allows users to find data sets and build various models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
Kaggle provides various opportunities using their site people can access for machine learning programs and data analysis.Kaggle helps easy to work with large of data sets and helps company for better decesion making.
Kirti Mehta
Roll no 19 B div
2GI19MBA43
Kaggle, the Google acquired data Science platform, started as a virtual meeting point for machine learning geeks to compete on predictive accuracy scores.
Despite being a free service, Kaggle can help address an increasing number of data challenges :
1) how to find reliable data sources to enrich existing customer and marketing data
2) how to find ideas, inspiration and relevant code for a new data analysis without reinventing the wheel
3) how to collaborate efficiently on a data project with colleagues
4) how to apply machine learning and artificial intelligence to marketing analytics projects.
Hence, basically their goal is to leverage the collective intelligence of thousands of data scientists around the world to solve a data problem.
Nikhila Rattu USN:2GZ19MBA01
Kaggle supports a variety of dataset publication formats, it strongly encourage dataset publishers to share their data in an accessible, non-proprietary format if possible. The accessible data formats are better supported on the platform, they are also easier to work with for more people regardless of their tools.This helps us to learn why and how to make less well supported file types as accessible as possible to the data science community.
Kirti Mehta
Roll no 19 B div
2GI19MBA43
Kaggle, the Google acquired data Science platform, started as a virtual meeting point for machine learning geeks to compete on predictive accuracy scores.
Despite being a free service, Kaggle can help address an increasing number of data challenges :
1) how to find reliable data sources to enrich existing customer and marketing data
2) how to find ideas, inspiration and relevant code for a new data analysis without reinventing the wheel
3) how to collaborate efficiently on a data project with colleagues
4) how to apply machine learning and artificial intelligence to marketing analytics projects.
Hence, basically their goal is to leverage the collective intelligence of thousands of data scientists around the world to solve a data problem.
Nilesh Gavande
USN: 2GZ19MBA02
Div:B
R.no:28
I✓dentify a valuable machine learning problem that you have the data for.
✓You can compete on many problems.
✓The competition host prepares the data and a description of the problem. ✓Participants experiment with different techniques and compete against each other to produce the best models.
✓Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas.
Job point is correct
Ninad Patil (2GZ19MBA03)
1.Participants experiment with different techniques and compete against each other to produce the best models. Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas. Submissions can be made through Kaggle Kernels, through manual upload or using the Kaggle API. For most competitions, submissions are scored immediately (based on their predictive accuracy relative to a hidden solution file) and summarized on a live leaderboard.
2.The competition host prepares the data and a description of the problem.
3. After the deadline passes, the competition host pays the prize money in exchange for "a worldwide, perpetual, irrevocable and royalty-free license to use the winning Entry", i.e. the algorithm, software and related intellectual propertydeveloped, which is "non-exclusive unless otherwise specified".
Anushree Sinai Navelkar
2GZ19MBA37
Roll no 49
Kaggle a platform for data science competitions,can be intimidating for beginners to get into.
Top team boast decades of combined experience,tackling ambitious problems such as to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers.
Various features to be handled
1. These are usually sponsored by companiwc, organisations,or even government.They have largest prize pool.
2. These are research orientated and have little to no prize money. They also have non traditional submission processes.
3. These are sponsored by companies who want to hire data scientists. These are still relatively uncommon.
Kaggle also helps :
1. Each competition is self contaunco you don't need to scope your own project or collect data,which helps you to focus on other skills.
2. The best way to learn data science is by doing as long as you don't stress out about winning every problem you can still practice interesting problems.
3. discussion and winner interviews are enlightened each competition has it's own discussion board and debriefs with the winners. You can peek into the thought proccess of more experienced data scientists.
Third point is highlight of this post
Naveen KumarM
Roll:25
USN:2GI19MBA57
1.Kaggle got its start in 2010 by offering machine learning competitions.
2.Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
3.Kaggle allows users to find and publish data sets, explore and build models in a web-based dat, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
4.Kaggle's first product Companies post problems and machine learners compete to build the best algorithm.
Third point is a nice one
Absolutely right
Divya V Palankar
USN-2GI19MBA025
Kaggle is an online community of data scientist and machine learning practitioners. Kaggle got start in 2010 by offering machine learning competition and now also offers a public data plat form, cloud based workbench of data science and artificial intelligence education.
Participants experiment with different techniques and compet against each other to produce the best models. Work is shared publicly through kaggle kernels to achieve a better benchmark and to inspire new ideas
Several academics papers have been published on the basis of finding made in kaggle competition. A key to this is effect of the leaderboard which encourages to participants to continue innovating beyond existing best practices.
Use simple words, others should understand. For example data mingling other may not understand
SRIKUMAR PATIL
USN:2GZ19MBA43
Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems.
The importance of the data lies in consistency and continual growth. It enables companies to create new business opportunities and generate more revenues and produce actionable insights.They even make or break the decisions of the company.
sharvari agnihotri
Roll no 44 division - b
kaggle is a website that hosts machine learning competitions.Along with competitions it also hosts following three important things:
1 Data sets :
Even the ones not related to any competition it houses 9500+ data sets as compared to 300 competitions at a time of writing.So you can sharpen your skills with whatever dats sets amuses or interests you.
2 kernels:
They are just kaggle' s version of Jupyter notebooks which I turn are really effective and cool way of sharing code along with lots of visualisations and outputs.
3 learn:
This tab contains free practical hand on courses that cover the minimum prerequisites needed to quickly get started in the field.
How do they help organisations in Decsion making?
- Enterprises today have access to various kinds of data from the touchpoint of customers including websites,business apps,social media pages, blogs,etc. However, just gathering the data is not enough for positive impact on business. There is need to analyse and collate data into pieces of value added information. It is used in following ways for decision making by organisations:
• Improve customer engagement retention:
As the data from various sources is collected from customer touchpoint it can be analysed further and Decisions can be made about what exactly are the customers demanding and their requirements. Companies have been using real time data to one to one personalized services.
•Enhance operational efficiency:
Today companies are leveraging data to automate processes optimize effienciency of their businesses.For example, Tesla's are embedded with sensors that collect data and send it to the central servers for analysis.
• Increased capacity without extra investment:
Telecommunication companies uses big data analytics to reduce network errors,optimise resources and improving customer experience with the real time data.
This Merk European drug company has improved their formulations using Kaggle competition is as follows:
1. It is a machine learning engineer and has helped Merk a European company to improve its technology as per latest trends in market so that day to day transactions are been recorded.
2. Here through Kaggle work is shared publicly and help us to achieve benchmark in the market. and help them to solve the problems.
3. Kaggle helps this company to have a data science environment in their company so that they can easily access the drugs all over the world.
Kaggle helps connect recruiters and candidates through their Job board.
The company also creates incentives for collaboration, and has fostered an open and welcoming community that encourages helping each other to produce better algorithms and results which also helps in mutual problem solving.
Kaggle is also becoming a repository of vast, clean, and easy to work with datasets. This makes the company get a huge information access through the vast datasets.
Anusha vibhute
2GI19MBA13
mindset that techniques, objectives, and processes prioritized in Kaggle competitions reflect those in a typical business environment.
Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems
The biggest challenge with this mindset is that there are core fundamental differences between Data Science used in Kaggle competitions and that practiced in an industry setting (what I call Industry Data Science). I will go into three specific reasons why this is the case, and how we can set the right expectations for those who are transitioning into the field.
Kaggle allowing anyone to get their hands on real-world data and giving them the opportunity to solve hard machine learning challenges .so using the real world dada the decision making and forecasting becomes easy and even kaggle provides immense cputational power through their servers which is very helpfulKaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems.
Kaggle is platform to complete with others in competition which are based on machine learning tasks.you may know about codechef ,Hackerrank etc..so kaggle is also like them,but the key difference is the competition are only related to machine learning,data science,deep learning or AI related.
You are right kaggle helping medical field in a great wau
• The competition host prepares the data and a description of the problem.
• Participants experiment with different techniques and compete against each other to produce the best models.
• Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas.
Kaggle is a very popular platform that’s great for aspiring Data Scientists to pick up skills on applied Machine Learning: preprocessing, pipelining, algorithm optimization.
Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
Very nice
Sir it uses decision tree model. The rain data is distributed according to the area, location, average rain fall, previous years rainfall and then compares such parameters with the present data.
Kaggle started in the 2010 by offering machine learning competitions and now also offers a public data platform, a cloud-based workbench for data science, and Artificial Intelligence education.
Kaggel is a platform for predictive modeling and analytics compitition in which companies and researchers post data miners compete to produce the best models for predicting and describing the data.
Shreya sainuche
2GZ19MBA34
Kaggle got its start in 2010 offering machine learning competitions and now aslo offers a public data platform. A cloud based workbench for data science and artificial intelligence education.kaggle has run hundreds of machine learning competitors.competitons have resulted in many successful projects including furthering the state of the art in HIV research,chess ratings and traffic forecasting.
Ashwini Ramesh
2GI19MBA16
B div
Kaggle is platform to compete with others in competitions which are based on machine learning tasks. You may know about Codechef, Hackerrank etc., so kaggle is also like them, but the key difference is the competition are only related to machine learning, data science, Deep learning or AI related.Well using Kaggle is really good thing for learning some trends and techniques in machine learning or data science. If you are really good in data science then I would suggest you to take part in competition. You will find dozens of them on Kaggle. If you are not really good in data science then you should use Kaggle for learning purpose. You can read blogs, interviews of grand masters and winners of different competitions. You can read articles related to some techniques in data science. And when you get comfortable with data science then go to competition section and take part in competition.
Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
2GZ19MBA50
*Kaggle is a online platform which hosts machine learning and data science competitions which helps organisation solve their real life problems. Kaggle holds half a million data scientists on its platform.
*Once an organization has made its data available via Kaggle Prospect, members of the Kaggle community can submit suggestions and analyses about how the data can be used (“data prospecting”). Kaggle can tailor the results of this data prospecting to match the client’s desire, whether it be developing predictive modeling problems or creating a data visualization
*Kaggle’s community of nearly 40,000 data scientists will comment and discuss the data set in a collaborative forum. The Kaggle community at large can vote for the ideas and suggestions they expect to draw the most value out of the data, and a panel of judges from the client organization will analyze the top ideas and select a winner. When data prospecting results in a well-posed predictive modeling question, the organization can choose to run a competition on Kaggle immediately.
Superb example
2GZ19MBA18
Roll no. 37
Excellent answer
1) kaggle provide reliable data to the organisation while decision making.
2) kaggle is more valuable than prediction.
3) kaggle helps in building the trust in your decision.
Innovation technique is high light of the post
1)The competition host prepares the data and a description of the problem.
2)Participants experiment with different techniques and compete against each other to produce the best models. Work is shared publicly through Kaggle Kernels to achieve a better benchmark and to inspire new ideas. Submissions can be made through Kaggle Kernels, through manual upload or using the Kaggle API. For most competitions, submissions are scored immediately (based on their predictive accuracy relative to a hidden solution file) and summarised on a live leaderboard.
3)After the deadline passes, the competition host pays the prize money in exchange for "a worldwide, perpetual, irrevocable and royalty-free license to use the winning Entry", i.e. the algorithm, software and related intellectual property developed, which is "non-exclusive unless otherwise specified".
Business Description
1)Organization is engaged in providing computer peripherals, parts, memory cards, clinical instrument, medical lab items and clinical softwares. Main Income is from products and services.
2)Company is engaged in providing Revenue Cycle Management, tax management, IT sotware services, and finance and accounting BPO. Main Income is from pharma companies billing and revenue, finance services.
3)The organization is engaged in R&D projects to licensed technologies for the Group's businesses in collaboration with its technology, production, environment setup and marketing divisions(engineering, life sciences and material sciences). Main income is from retainership fees and manufacturing unit setups.
4)Company is engaged in providing security surveillance, detective services and research areas. Mian income is from security deveoped products and R&D services.
Write in third party mode
Sanket.S.Sunthankar
2GZ19MBA31
Div:B
The benefits of Kaggle are:
1. Can publish high quality data set.
2. Can get you Feedback directly through forums from different experts
3. Free data science and machine learning courses.
4. Making use of Data from famous companies and non profit organizations
5. Usage of all types of data such as customer data,log files, timeseries, html pages, images and documents
The examples of machine learning competitions which help organization make decisions using kaggle database :
1.Predicting compound toxicity given its molecular structure
2. Automatically grading student written essays
3. Personalizing web search results
4. Detecting diabetic retinopathy
Correct
Karan Mane.
Usn-2GI19MBA37
The importance of the data lies in consistency and continual growth. It enables companies to create new business opportunities and generate more revenues and produce actionable insights.
They even make or break the decisions of the company.
Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. You can compete on many problems.
Akshata halagannavar
USN: 2GI19MBA08
Roll no. 4 (A div)
Inside Kaggle you’ll find all the code & data you need to do your data science work. Use over 19,000 publicdatasets and 200,000 publicnotebooks to conquer any analysis in no time.
Kaggle’s model is based on presenting machine learning competitions that function as opportunities for machine learning enthusiasts to test out, and further develop, their skills. From a learning perspective, this makes a great deal of sense, and the elements of play and competition add layers of motivation and excitement. The real key to Kaggle’s success, however, is that these competitions rely on real-world data provided by real-world companies.
The increasingly symbiotic relationship between companies that need machine learning expertise, and data science competition platforms like Kaggle, has greatly impacted how rapid advancement is being achieved. This relationship has also changed the hiring landscape. Companies today face ever-increasing pressure to innovate in order to remain competitive, and they are pursuing comparatively unconventional means for discovering and attracting new talent in order to maintain their edge. The need for machine learning talent is so great, that companies are looking far further afield than once they might have.
Vishal kurade 2GZ19MBA53
Kaggle’s model is based on presenting machine learning competitions that function as opportunities for machine learning enthusiasts to test out, and further develop, their skills. Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.kaggle provides platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
Today many data scientists are working on covid 19 using kaggle
Kaagle helps in providing variety of data publication format. It helps us to start data science projects, and also allows us to find and publish high quality data set, hence it aslo help us in building Codes and Models.
Kaagle provide a data set referring to which the organisation can take various decission.
1.It is an online learning aap where we can
Choose any course and buit our skills.
2.if here we can try learning different
techniques and compete with other
participants by producing best and
innovative models.
3.it helps in machine and artificial
intelligence learning.
4.Kaagle provides opportunities to the
people in web based data science
environment.
5.Kaagle provides an option where
participants can share their work
publically which sets a benchmark to
inspire new and innovative ideas
Kaggle also supports special BigQuery Datasets. BigQuery is a “big data” SQL store invented by Google. Many massive public datasets, like all the code in GitHub and the complete history of the Bitcoin blockchain, are available publically through the Google BigQuery Public Datasets initiative. Some of these are in turn also available as Kaggle Datasets!
Kaggle, an online community for data scientists and a platform for data science competitions, has unveiled a new and timely bounty-paying challenge: the Covid-19 Open Research Dataset Challenge, or CORD-19.
CORD-19 asks artificial intelligence (AI) and machine learning researchers to develop text and data mining tools to analyse a dataset comprising tens of thousands of articles on virology and infectious disease. The goal is to help provide answers for 10 tasks, or lines of inquiry about the disease.
The prize for each of the tasks in the CORD-19 challenge is $1000, delivered as cash or as a charitable donation to research and relief efforts.
The world isn’t lacking for research about Covid-19. Kaggle’s dataset contains “over 29,000 scholarly articles, including over 13,000 with full text, about Covid-19, SARS-CoV-2, and related coronaviruses,” according to the challenge introduction.
But there’s little time to paw manually through those haystacks of research for the needles we need, so Kaggle is encouraging the use of machine learning techniques like natural language processing to get relevant data into the right hands more quickly.
1) kaggle provide reliable data to the organisation while decision making.
2) kaggle is more valuable than prediction.
3) kaggle helps in building the trust in your decision.
Neha Hundre
2GI19MBA59
Roll no :26
Kaggle is an online community of data scientists and machine learning practitioners. It allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers.
Machine learning was Kaggle's first product. Companies post problems and machine learners compete to build the best algorithm.
It has resulted in many successful projects including furthering the state of the art in HIV research, chess ratings and traffic forecasting.
Kaggle is a base to compete with others in competition which are mainly based on machine learning tasks.In this kaggle competition are only based on machine learning and data science. Using kaggle helps for learning some trends and techniques in machine learning. You can also take kaggle for learning of machine learning and data science.
How it helps to business organisation ?
1 As a kaggle is a base for machine learning and data science, it connects companies facing hard problems with data scientists who can solve them.
2 participants experiments the given problems with different technique and compete against each other to get best result.
3 The competitions often comes with money price, job opportunity and also it helps to learn new participants to learn. In this kaggle.
4 Kaggle enables tha data scientists and other developers to engage in running machine learning contests, write and share code and to host datasets.
5 There are currently over one million kaggle members. And this data community has submitted above 4 million learning models.
6 We can get interesting and challenging projects where the participants van practice.
Sneha Rajput
2GZ19MBA38
Roll. No 48(B)
*Kaggle is a platform for doing and sharing.
*It's all about google platform which host the competition, datasets, discussion regarding machine learning in different area's.
Business organization can improve there decision by using kaggle
*Where organization can do lot of data science and machine learning without heating up there systems.
*The organization can publish high quality datasets on kaggle.
* Kaggle has greatly impacted how rapid advancement is being achieved.
*Kaggle is a really great distribution platform for innovative techniques.
*The benefits of being active on Kaggle are not just limited to the rich set of problems available, and the support from the community.
YAMANAPPA METRI
USN:2GZ19MBA55
ROLL NO:58
DIV:A
Kaggle got its start in 2010 by offering machine learning competitions and now also offers a public data platform, a cloud-based workbench for data science, and Artificial Intelligence education. Its key personnel were Anthony Goldbloom and Jeremy Howard. Nicholas Gruen was founding chair succeeded by Max Levchin. Equity was raised in 2011 valuing the company at $25 million. On 8 March 2017, Google announced that they were acquiring
Personalized customer experiences. One of the benefit of kaggle could be the ability for sales and marketing teams to understand their audience on a very granular level. With this knowledge, an organization can create the best possible customer experiences.
Jyoti bhadaganvi
USN 2GI19MBA36 (A)
Kaggle helps business organizations to take effective decisions the following are reasons how it will improve the organization decisions.
1.it provides description of the problem and helps to take different techniques to produce best models.
2.understand and analyze the business problems.
3.machine learning competition company can post the problem to build best algorithm.
4. Its helps to develop software and intellectual property development.
Yes Sir. I think 15 mins is the time limit.
Sairaj Aihole
Usn: 2GZ19MBA27
Kaggle is a platform for predictive modelling analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. and
You can use it in following ways:
1. Competitions | Kaggle
You can compete on many problems. Find the
problems you find interesting and compete to provide better solution to the problem.
2. Datasets Kaggle The best place to discover and seamlessly analyze open data. You can find any dataset of your interest and apply analytical methods to fine tune your analytical capabilities.
3. Kernels Kaggle Allows, user to share and learn from different approaches.
Rahul Patil
USN- 2GZ19MBA22
Kaggle’s model is based on presenting machine learning competitions that function as opportunities for machine learning enthusiasts to test out, and further develop, their skills. From a learning perspective, this makes a great deal of sense, and the elements of play and competition add layers of motivation and excitement. The real key to Kaggle’s success, however, is that these competitions rely on real-world data provided by real-world companies.
The importance of the data lies in consistency and continual growth. It enables companies to create new business opportunities and generate more revenues and produce actionable insights.They even make or break the decisions of the company.
Hayawadan
USN : 2GI19MBA33
Kaggle helps organization in many ways to help in decision making and some of them are as follows :
1) Kaggle helps in handling massive file sizes also for sampling and extracting useful subsets of data
2) Kaggle leaderboard ranking is immediate feedback on how well you have broken down and solved the problem
Raghotam chimmalagi
Usn 2GZ19MBA21 (A)
The importance of the data lies in consistency and continual growth. It enables companies to create new business opportunities and generate more revenues and produce actionable insights.
They even make or break the decisions of the company.
Kaggle is a platform to compete with others in competition which are based on machine learning tasks. Where the machine learning algorithms are used and desion tree ,apriori algorithms are used for the decision making fir the business units
Prachi shivangekar
2GZ19MBA14
Kaggle is the perfect platform to learn from other data scientist all over the world and share your knowledge. This platform grown to become the largest data science community in the world.
Kaggle contributors, who had the opportunity to work in a team , teamt also benefits kaggles by exposing them two different tools and techniques helpful in solving data problems
Soumya Gouranna 2GZ19MBA41
Companies use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. Kaggle, a popular platform for data science competitions, can be intimidating for beginners to get into.
Kaggle competitions encourage you to squeeze out every last drop of performance, while typical data science encourages efficiency and maximizing business impact.
Kaggle has a cool feature in which participants can submit "kernels," which are short scripts that explore a concept, showcase a technique, or even share a solution.
Kaggle is a very popular platform that’s great for aspiring Data Scientists to pick up skills on applied Machine Learning: preprocessing, pipelining, algorithm optimization.
Kagglers often rely on complicated, multi-layered ML and Deep Learning approach for the competition. Specifically, they use stacking/blending, as it remains the most successful strategy for winning Kaggle competitions. Erin LeDell, the Chief Decision Scientist at H2O.ai, lays out this point in one of her seminars.
Name:Mumtaz Naik
USN:2GI19MBA54
Roll No.:24(A)
1)A Kaggle is a gaggle of data scientists.
2)Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data. We can compete on many problems.
3)The competition host prepares the data and a description of the problem. Participants experiment with different techniques and compete against each other to produce the best models. Work is shared publicly through Kaggle Kernels.
4)We can read articles related to some techniques in data science. And when we get comfortable with data science then go to competition section and take part in competition.
5)Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
1. Kaggle exposes you to a wide range of machine learning problems such as forecasting, sentiment analysis, natural language processing, image recognition, etc. This motivates you to learn as much as you can about the problem domain, the type of data involved, and the various algorithms which may be applicable.
2. Kaggle is under a time limit. This 'forces' you to work in a very efficient manner in developing and testing out alternative ideas quickly.
3. Kaggle helps in learning the value of cross-validation. Re-sampling and retraining your model multiple times to validate that your solution is working and not over-fitting the data.
4. Kaggle competitions force you to code and recode your solution in most resource efficient manner possible. All these features of kaggle helps in better decision making process.
Amit paripatyadar
Roll 05
A div
It's all about google platform which host the competition, datasets, discussion regarding machine learning in different area's.Kaggle helps business organizations to take effective decisions
Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.As a kaggle is a base for machine learning and data science, it connects companies facing hard problems with data scientists who can solve them.
Kaggle can help address an increasing number of data challenges:
1.How to find reliable data sources to enrich existing customer and marketing data.
2.How to find ideas, inspiration, and relevant code for a new data analysis without reinventing the wheel.
3.How to collaborate efficiently on a data project with csolleagues.
4.How to apply machine learning and artificial intelligence to marketing analytics projects.
Pavitra Hubballi
B Division
Usn: 2GZ19MBA10
Anup Yankati
Roll no 06
2GI19MBA12
Kaggle helps connect recruiters and candidates through their Job board.
The company also creates incentives for collaboration, and has fostered an open and welcoming community that encourages helping each other to produce better algorithms and results which also helps in mutual problem solving.
Kaggle is also becoming a repository of vast, clean, and easy to work with datasets. This makes the company get a huge information access through the vast datasets.
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