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Kaggle
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<h2 id="history">History</h2> <p>Kaggle was founded by <a href="/facts/Anthony_Goldbloom/ld4ygmub">Anthony Goldbloom</a> in April 2010.<a class="footnote-ref" id="fnref:2" href="#fn:2"><sup>2</sup></a> <a href="/facts/Jeremy_Howard_(entrepreneur)/PoM1o6DK">Jeremy Howard</a>, one of the first Kaggle users, joined in November 2010 and served as the President and Chief Scientist.<a class="footnote-ref" id="fnref:3" href="#fn:3"><sup>3</sup></a> Also on the team was <a href="/facts/Nicholas_Gruen/rSkJ923Y">Nicholas Gruen</a> serving as the founding chair.<a class="footnote-ref" id="fnref:4" href="#fn:4"><sup>4</sup></a> In 2011, the company raised $12.5 million and <a href="/facts/Max_Levchin/P37WW8f9">Max Levchin</a> became the chairman.<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a> On March 8, 2017, <a href="/facts/Fei-Fei_Li/IUYLlzTH">Fei-Fei Li</a>, Chief Scientist at Google, announced that <a href="/facts/Google/GT9Sugza">Google</a> was acquiring Kaggle.<a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a> </p><p>In June 2017, Kaggle surpassed 1 million registered users, and as of October 2023, it has over 15 million users in 194 countries.<a class="footnote-ref" id="fnref:7" href="#fn:7"><sup>7</sup></a><a class="footnote-ref" id="fnref:8" href="#fn:8"><sup>8</sup></a><a class="footnote-ref" id="fnref:9" href="#fn:9"><sup>9</sup></a> </p><p>In 2022, founders Goldbloom and Hamner stepped down from their positions and D. Sculley became the <a href="/facts/Chief_executive_officer/mg4A8y5M">CEO</a>.<a class="footnote-ref" id="fnref:10" href="#fn:10"><sup>10</sup></a> </p><p>In February 2023, Kaggle introduced Models, allowing users to discover and use pre-trained models through deep integrations with the rest of Kaggle’s platform.<a class="footnote-ref" id="fnref:11" href="#fn:11"><sup>11</sup></a> </p> <h2 id="site-overview">Site overview</h2> <h3>Competitions</h3> <p>Many <a href="/facts/Machine-learning/e0w0XJTu">machine-learning</a> competitions have been run on Kaggle since the company was founded. Notable competitions include gesture recognition for <a href="/facts/Microsoft_Kinect/dD5P9XDW">Microsoft Kinect</a>,<a class="footnote-ref" id="fnref:12" href="#fn:12"><sup>12</sup></a> making a <a href="/facts/Soccer/yttjeD0D">football</a> <a href="/facts/Artificial_intelligence/lJGauQwX">AI</a> for <a href="/facts/Manchester_City_F.C./wtCrlIju">Manchester City</a>, coding a trading algorithm for <a href="/facts/Two_Sigma_Investments/3aMCWJ6Q">Two Sigma Investments</a>,<a class="footnote-ref" id="fnref:13" href="#fn:13"><sup>13</sup></a> and improving the search for the <a href="/facts/Higgs_boson/3LAYXfft">Higgs boson</a> at <a href="/facts/CERN/y1gwRchm">CERN</a>.<a class="footnote-ref" id="fnref:14" href="#fn:14"><sup>14</sup></a> </p><p>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, via manual upload or using the Kaggle <a href="/facts/Application_programming_interface/GMlN4vUr">API</a>. 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 <a href="/facts/Intellectual_property/PqHW9mVP">intellectual property</a> developed, which is "non-exclusive unless otherwise specified".<a class="footnote-ref" id="fnref:15" href="#fn:15"><sup>15</sup></a> </p><p>Alongside its public competitions, Kaggle also offers private competitions, which are limited to Kaggle's top participants. Kaggle offers a free tool for data science teachers to run academic machine-learning competitions.<a class="footnote-ref" id="fnref:16" href="#fn:16"><sup>16</sup></a> Kaggle also hosts recruiting competitions in which data scientists compete for a chance to interview at leading data science companies like <a href="/facts/Facebook/0IhXFR6u">Facebook</a>, <a href="/facts/Winton_Group/7cnNLgms">Winton Capital</a>, and <a href="/facts/Walmart/E6dPQV2m">Walmart</a>. </p><p>Kaggle's competitions have resulted in successful projects such as furthering <a href="/facts/HIV/ulY2rgzu">HIV</a> research,<a class="footnote-ref" id="fnref:17" href="#fn:17"><sup>17</sup></a> <a href="/facts/Chess/47ykvkHF">chess</a> ratings<a class="footnote-ref" id="fnref:18" href="#fn:18"><sup>18</sup></a> and <a href="/facts/Traffic/cHx4tMo1">traffic</a> forecasting.<a class="footnote-ref" id="fnref:19" href="#fn:19"><sup>19</sup></a> <a href="/facts/Geoffrey_Hinton/HJU6lC2H">Geoffrey Hinton</a> and George Dahl used deep <a href="/facts/Neural_networks/DDhJTfMc">neural networks</a> to win a competition hosted by <a href="/facts/Merck_%2526_Co./8YD8dvwR">Merck</a>. Vlad Mnih (one of Hinton's students) used deep neural networks to win a competition hosted by <a href="/facts/Adzuna/hJUzrgUm">Adzuna</a>. This resulted in the technique being taken up by others in the Kaggle community. Tianqi Chen from the <a href="/facts/University_of_Washington/36PG6qkG">University of Washington</a> also used Kaggle to show the power of <a href="/facts/Xgboost/YupgXmfH">XGBoost</a>, which has since replaced <a href="/facts/Random_forest/Ff1ppJEQ">Random Forest</a> as one of the main methods used to win Kaggle competitions. </p><p>Several academic papers have been published based on findings from Kaggle competitions.<a class="footnote-ref" id="fnref:20" href="#fn:20"><sup>20</sup></a> A contributor to this is the live leaderboard, which encourages participants to continue innovating beyond existing best practices.<a class="footnote-ref" id="fnref:21" href="#fn:21"><sup>21</sup></a> The winning methods are frequently written on the Kaggle Winner's Blog. </p> <h3>Progression System</h3> <p>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, datasets, kernels (code-sharing), and discussions.<a class="footnote-ref" id="fnref:22" href="#fn:22"><sup>22</sup></a> </p><p>The highest tier, Kaggle Grandmaster, is awarded to users who have ranked at the top of multiple competitions including high ranking in a solo team. As of April 2, 2025, out of 23.29 million Kaggle accounts, 2,973 have achieved Kaggle Master status and 612 have achieved Kaggle Grandmaster status.<a class="footnote-ref" id="fnref:23" href="#fn:23"><sup>23</sup></a> </p> <h2 id="see-also">See also</h2> <ul><li><a href="/facts/Data_science_competition_platform/5vWGA3UM">Data science competition platform</a></li> <li><a href="/facts/Anthony_Goldbloom/ld4ygmub">Anthony Goldbloom</a></li> <li><a href="/facts/Hugging_Face/h8kkdUus">Hugging Face</a></li></ul> <h2 id="further-reading">Further reading</h2> <ul><li><a href="https://obamawhitehouse.archives.gov/blog/2011/06/27/competition-shines-light-dark-matter">"Competition shines light on dark matter", Office of Science and Technology Policy, Whitehouse website, June 2011</a></li> <li><a href="https://www.wsj.com/articles/SB10001424052748704662604576202392747278936">"May the best algorithm win...", <i>The Wall Street Journal</i>, March 2011</a></li> <li><a href="https://www.newscientist.com/blogs/onepercent/2011/07/kaggle-competition-aims-to-giv.html">"Kaggle contest aims to boost Wikipedia editors", <i>New Scientist</i>, July 2011</a> <a href="https://web.archive.org/web/20160322012136/https://www.newscientist.com/blogs/onepercent/2011/07/kaggle-competition-aims-to-giv.html">Archived</a> 2016-03-22 at the <a href="/facts/Wayback_Machine/nmQ3a6JC">Wayback Machine</a></li> <li><a href="http://www.nature.com/nbt/journal/v29/n9/full/nbt.1968.html">"Verification of systems biology research in the age of collaborative competition", <i>Nature Nanotechnology</i>, September 2011</a></li></ul> <h2 id="references">References</h2> <ol> <li id="fn:1"><p>"A Beginner's Guide to Kaggle for Data Science". MUO. 2023-04-17. Retrieved 2023-06-10. <a href="https://www.makeuseof.com/beginners-guide-to-kaggle/" target="_blank">https://www.makeuseof.com/beginners-guide-to-kaggle/</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li> <li id="fn:2"><p>Lardinois, Frederic; Mannes, John; Lynley, Matthew (March 8, 2017). "Google is acquiring data science community Kaggle". Techcrunch. Archived from the original on March 8, 2017. Retrieved March 9, 2017. <a href="https://techcrunch.com/2017/03/07/google-is-acquiring-data-science-community-kaggle/" target="_blank">https://techcrunch.com/2017/03/07/google-is-acquiring-data-science-community-kaggle/</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li> <li id="fn:3"><p>"The exabyte revolution: how Kaggle is turning data scientists into rock stars". Wired UK. ISSN 1357-0978. Archived from the original on 30 September 2023. 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