The surge in interest in machine learning is due to the fact that it revolutionizes automation by learning patterns in data and using them to make predictions and decisions. If you're interested in machine learning, this book will serve as your entry point.

This edition of Python Machine Learning By Example begins with an introduction to important concepts and implementations using Python libraries. Each chapter of the book walks you through an industry-adopted application. You'll implement machine learning techniques in areas such as exploratory data analysis, feature engineering, and natural language processing (NLP) in a clear and easy-to-follow way.

With the help of this extended and updated edition, you'll learn how to tackle data-driven problems and implement your solutions with the powerful yet simple Python language, and popular Python packages and tools such as TensorFlow, scikit-learn, Gensim, and Keras. To aid your understanding of popular machine learning algorithms, this book covers interesting and easy-to-follow examples such as news topic modeling and classification, spam email detection, and stock price forecasting.

By the end of the book, you'll have put together a broad picture of the machine learning ecosystem and will be well-versed with the best practices of applying machine learning techniques to make the most out of new opportunities.