What this book covers
Chapter 1, Introducing Machine Learning with scikit-learn, is a brief introduction to the different types of machine learning and its applications.
Chapter 2, Predicting Categories with K-Nearest Neighbors, covers working with and implementing the k-nearest neighbors algorithm to solve classification problems in scikit-learn.
Chapter 3, Predicting Categories with Logistic Regression, explains the workings and implementation of the logistic regression algorithm when solving classification problems in scikit-learn.
Chapter 4, Predicting Categories with Naive Bayes and SVMs, explains the workings and implementation of the Naive Bayes and the Linear Support Vector Machines algorithms when solving classification problems ...
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