Sách/BookAuthors: Aurélien Géron (2022)
Third edition, explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started: Use Scikit-learn to track an example ML project end to end; Explore several models, including support vector machines, decision trees, random forests, and ensemble methods; Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection. 
