Last Updated on August 15, 2020 What if you could use a predictive model to find new combinations of attributes that do not exist in the data but could be valuable. In Chapter 10 of Applied Predictive Modeling, Kuhn and Johnson provide a case study that does just this. It’s a fascinating and creative example of how to use a predictive model. In this post we will discover this less obvious use of a predictive model and the types of […]

Last Updated on June 7, 2016 David Kofoed Wind posted an article to the Kaggle blog No Free Hunch titled “Learning from the best“. In the post, David summarized 6 key areas related to participating and doing well in competitive machine learning with quotes from top performing kagglers. In this post you will discover the key heuristics for doing well in competitive machine learning distilled from that post. Learning from the bestPhoto by Lida, some rights reserved Learning from Kaggle […]

Last Updated on June 7, 2016 The predictions you make with a predictive model do not matter, it is the use of those predictions that matters. Jeremy Howard was the President and Chief Scientist of Kaggle, the competitive machine learning platform. In 2012 he presented at the O’reilly Strata conference on what he called the Drivetrain Approach for building “data products” that go beyond just predictions. In this post you will discover Howard’s Drivetrain Approach and how you can use […]

Last Updated on June 7, 2016 Jeremy Howard, formally of Kaggle gave a presentation at the University of San Francisco in mid 2013. In that presentation he touched on some of the broader benefits of machine learning competitions like those held on Kaggle. In this post you will discover 5 points I extracted from this talk that will motivate you to want to start participating in machine learning competitions Competitive Machine Learning is a MeritocracyPhoto by PaulBarber, some rights reserved […]