Top Machine Learning books curated by experts

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification.

Python Machine Learning is a comprehensive guide to machine learning, deep learning, and data analysis using Python. In this book, Sebastian Raschka and Vahid Mirjalili provide practical knowledge and techniques for creating and contributing to modern data analysis.

By using concrete examples, minimal theory, and two production-ready Python frameworksâ??Scikit-Learn and TensorFlowâ??author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. Youâ??ll learn a range of techniques, starting with…

Key Features
Design, train, and evaluate machine learning algorithms that underpin automated trading strategies
Create a research and strategy development process to apply predictive modeling to trading decisions
Leverage NLP and deep learning to extract tradeable signals from market an…

Laurence Moroney's “AI and Machine Learning for Coders” is an invaluable guide for programmers looking to transition into the exciting world of AI. This book empowers readers to implement common AI scenarios such as computer vision, NLP, and sequence modeling by taking a practical, code-first ap…

“Artificial Intelligence: A Modern Approach” goes beyond the basics and delves into advanced topics in AI. It covers natural language processing, an area concerned with enabling computers to understand and generate human language. The book explores techniques for parsing, semantic analysis, and …

Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.

Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis.

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental…

It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples o

How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learni…

Machine Learning for Humans is an introduction to machine learning that is accessible to anyone with a basic understanding of high school mathematics. The book provides a practical understanding of machine learning through a hands-on approach, using Python as the programming language.

AWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud.

An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement le…

Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniq…