This article contains content that is written like an advertisement. (February 2022)
|Founder||Anthony Goldbloom, Ben|
|Headquarters||San Francisco, United States|
|Anthony Goldbloom (CEO)|
Ben Hamner (CTO)
Jeff Moser (Chief Architect)
|Products||Competitions, Kaggle Kernels, Kaggle Datasets, Kaggle Learn|
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.
Kaggle was first launched 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 the founding chair succeeded by Max Levchin. Equity was raised in 2011 valuing the company at $25.2 million. On 8 March 2017, Google announced that they were acquiring Kaggle.
In June 2017, Kaggle claimed it surpassed 1 million registered users and, as of 2021, over 8 million. The users come from 194 countries.
By March 2017, the Two Sigma Investments fund was running a competition on Kaggle to code a trading algorithm.
- The competition host prepares the data and a description of the problem; the host may choose whether it's going to be rewarded with money or be unpaid.
- 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.
- 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".
Alongside its public competitions, Kaggle also offers private competitions limited to Kaggle's top participants. Kaggle offers a free tool for data science teachers to run academic machine-learning competitions. Kaggle also hosts recruiting competitions in which data scientists compete for a chance to interview leading data science companies like Facebook, Winton Capital, and Walmart.
Many machine-learning competitions have been run on Kaggle since the company was founded. Notable competitions include one improving gesture recognition for Microsoft Kinect, making a football AI for Manchester City, and improving the search for the Higgs boson at CERN.
Competitions have resulted in successful projects such as furthering HIV research, chess ratings and traffic forecasting. Geoffrey Hinton and George Dahl used deep neural networks to win a competition hosted by Merck. Vlad Mnih (one of Hinton's students) used deep neural networks to win a competition hosted by Adzuna. This resulted in the technique being taken up by others in the Kaggle community. Tianqi Chen from the University of Washington also used Kaggle to show the power of XGBoost, which has since replaced Random Forest as one of the main methods used to win Kaggle competitions.
Several academic papers have been published on the basis of findings made in Kaggle competitions. A contributor to this is the live leaderboard, which encourages participants to continue innovating beyond existing best practices. The winning methods are frequently written on the Kaggle blog, Kaggle Winner's Blog.
Kaggle Progression System
Kaggle has implemented a progression system to recognize and reward users based on their contributions and achievements within the platform. This system consists of five tiers: Novice, Contributor, Expert, Master, and Grandmaster. Each tier is achieved by meeting specific criteria in competitions, kernels (code-sharing), and discussions.
The highest and most prestigious tier, Kaggle Grandmaster, is awarded to users who demonstrate exceptional skills in data science and machine learning. Achieving this status is extremely challenging. As of April 4, 2023, out of 12 million Kaggle users, only 2,331 (about 1 out of every 5500 users) have reached the Master level.
Among these Masters, only 422 (approximately 1 out of every 5 Masters) have achieved the coveted Kaggle Grandmaster status.
The other tiers in the progression system include:
- 13 thousand Experts
- 200 thousand Contributors
- 12 million Novices.
The progression system serves to motivate users to continuously improve their skills and contribute to the Kaggle community.
In February 2023, Kaggle introduced Models which allows users to discover and use pre-trained models through deep integrations with the rest of Kaggle’s platform.
In March 2017, Fei-Fei Li, Chief Scientist at Google, announced that Google was acquiring Kaggle during her keynote at Google Next.
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