Book Content
chapters • 5h44m total length
1. Introducing Machine Learning with scikit-learn
2. Predicting categories with K-Nearest Neighbours
3. Predicting categories with Logistic Regression
4. Predicting categories with Naive Bayes and SVMs
5. Predicting numeric outcomes with Linear Regression
6. Classification & Regression with Trees
7. Clustering data with Unsupervised Machine Learning
8. Performance evaluation methods














