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The book begins with an overview of the different types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. The authors then discuss the various data processing techniques that are essential for machine learning, such as data cleaning, feature engineering, and model selection.In the following chapters, the book covers a wide range of machine learning topics, including:Regression: A technique for predicting continuous target values.Classification: A technique for predicting categorical target values.Clustering: A technique for grouping similar data points together.Dimensionality reduction: A technique for reducing the number of features in a dataset.Model evaluation: A technique for assessing the performance of a machine learning model.The book also includes a chapter on deep learning, which is a subfield of machine learning that has gained popularity in recent years.