The site kaggle.com runs machine learning competitions, one of which is "Titanic: Machine Learning from Disaster" [0]. I haven't looked into the site myself; I

The site kaggle.com runs machine learning competitions, one of which is "Titanic: Machine Learning from Disaster" [0]. I haven't looked into the site myself; I learned about it from David Spiegelhalter's book "The Art of Statistics: Learning from Data" [1]. The competition's problem of predicting who would have survived the disaster provides much of the motivation for the chapter "Algorithms, Analytics and Prediction". In that chapter he applies "classification trees" to the problem, talks a bit about ROC (Receiver Operating Characteristic) curves, the problem of over-fitting, and other issues. (Overall, I thought it was a good, well-written popular math book. A bit more technical than average, but definitely not a textbook.) [0] https://www.kaggle.com/c/titanic https://www.kaggle.com/c/titanic [1] https://www.penguin.co.uk/books/294/294857/learning-from-data/9780241258767.html https://www.penguin.co.uk/books/294/294857/learning-from-dat...