Find The Best Machine Learning Textbooks | Expert Recommendations

By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and Tensor Flow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.

From the author of a world bestseller published in eleven languages, The Hundred-Page Machine Learning Book, this new book by Andriy Burkov is the most complete applied AI book out there. It is filled with best practices and design patterns of building reliable machine learning solutions that scale. Andriy Burkov has a Ph.D. in AI and is the leader of a machine learning team at Gartner. This book is based on Andriy’s own 15 years of experience in solving problems with AI as well as on the published experience of the industry leaders.

In this textbook, you can find pseudo-codes and written in an informal tone. The author begins with linear algebra and ends up with the latest innovation in various fields. Well defined and colorful images help you to understand the concepts clearly. The principled model-based approach has been discussed in depth. Upper-level undergraduate students and beginners can use this book.

If you are looking to go past the AI hype and understand everything about machine learning, then Machine Learning by Tom M. Mitchell should be the ideal pick. It is a top pick for those looking to get started with machine learning. The book provides an in-depth overview of the relevant theorems with pseudocode compilations of the respective algorithms. Another fantastic thing about The Machine Learning Book is its practical examples and case studies to simplify everything for the reader and help them grasp ml algorithms with ease. This book is a must-have for anyone looking to begin a career in machine learning. It has well-explained narratives, comprehensive explanations to ml basics and project-focused homework assignments. The book is also suitable for candidates taking machine learning courses or programs at all levels. – Topics covered in Machine Learning – Introduction to primary approaches to machine learning – Machine learning concepts and techniques – Genetic algorithms – Inductive logic programming – Reinforcement learning

I use this book often to onboard complete newbies at machine learning. Many of them are non-native English speakers. This book is written in plain English. No coding experience is required to understand it. It introduces core machine-learning-related algorithms with visual examples, and the explanations are simple and clear. Overall, it offers an excellent bird’s eye view of the art/science. It ends with further suggested reading.

Machine Learning is an excellent book for those looking for an uncomplicated but comprehensive introduction to the topic. It offers a good explanation of machine learning basics and features a wide number of examples and case studies that make it simpler for the reader to grasp and understand machine learning algorithms.

Machine Learning for Hackers is better suited for those who are more experienced in the understanding programming language. Most of the book is based on data analysis and also includes apposite case studies that do well to highlight the importance of using ML algorithms. Unlike most other books, it doesn’t dive too deep into mathematical theory but instead emphasizes real-life case studies and examples to help make the learning process proceed faster and more practical.

If you are looking for a quick entry into machine learning and also happen to have a good comprehension of engineering mathematics then this book is an excellent choice. It does well to impart sufficient knowledge about the various advanced theories and concepts of machine learning in an easy way to understand without being too lengthy or dense, it just gets straight to the point.