The book is divided into 10 chapters. It starts with an introduction to machine learning, then introduces representations and definitions, basic algorithms, principles of algorithms, basic best practices, natural language and deep learning, problems and solutions, advanced practices, unsupervised machine learning, other forms of learning, and conclusions. The book ends with a glossary of terms related to machine learning.
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