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Jeremy Howard President, Kaggle web Machine learning competitions Photo by mikebaird,

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Presentation on theme: "Jeremy Howard President, Kaggle web Machine learning competitions Photo by mikebaird,"— Presentation transcript:

1 Jeremy Howard President, Kaggle e-mail jeremy.howard@kaggle.com web www.kaggle.com Machine learning competitions Photo by mikebaird, www.flickr.com/photos/mikebaird Making data science a sport

2 Machine learning is everywhere… Insurance companies, banks, operations researchers, hedge funds, mutual funds, derivative analysts, computer scientists, health care organizations, physicians, geologists, astronomers, microbiologists, cosmologists, meteorologists, glaciologists, the federal bureau of investigation, actuaries, search engine companies, utilities, gambling casinos, defense departments, government planners, war games analysts, universities, fraud departments, tourist organizations, economists, sociologists, I-B-M-ers, programmers, politicians, marketing organizations, ad agencies, entertainment companies, physicists, central intelligence analysts, pharmacists, oil companies, mining companies, city planners, retailers, hotels, airlines, movie rental companies, leasing companies, tax planners, climate change researchers, game theorists, credit card companies, endowments, philanthropists, mathematicians, academicians, and philosophers...

3 …bit there’s a mismatch between those with data, and those with the skills to analyse it Crowdsourcing

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6 Global competitions 1½ weeks 70.8% Competition closes 77% State of the art 70% Predicting HIV viral load

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8 “In less than a week, Martin O’Leary, a PhD student in glaciology, outperformed the state-of-the-art algorithms” “The world’s brightest physicists have been working for decades on solving one of the great unifying problems of our universe” Kaggle’s Dark Matter Competition on the White House blog

9 User base: >32,000 registered data scientists

10 Our User Base

11 neural networks logistic regression support vector machine decision trees ensemble methods adaBoost Bayesian networks genetic algorithms random forest Monte Carlo methods principal component analysis Kalman filter evolutionary fuzzy modeling Users apply different techniques

12 Forecast Error (MASE) Existing model Tourism Forecasting Competition Aug 92 weeks later 1 month later Competition End

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14 Jeremy Howard j@kaggle.com


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