Book Content
chapters • 6h20m total length
1. Introduction to Test Driving Machine Learning
2. Neurotically test a neural network
3. Exploring the unknown with multi-armed bandits
4. Predicting values with regression
5. Making decisions black and white with logistic regression
6. Naïvely labeling with Naïve Bayes Classification
7. Optimizing by choosing a new algorithm (Random Forest)
8. Exploring SciKit-Learn test first
9. Bringing it all together
