In this article, I have compiled the best books for ML keeping absolute beginners in mind. These are the books I wish I had when I started with ML. Each of these books is extremely popular so you can choose the ones you like according to your liking. Let’s start!
Machine Learning For Absolute Beginners: A Plain English Introduction
The book organizes the theoretical and practical aspects of various ML techniques in very simple way which is great for a beginner. While this is not sufficient for anybody expecting to master the science, it’s a great start to look further.
Introduction to Machine Learning with Python: A Guide for Data Scientists
It focuses mostly on the Scikit-Learn library with an in-depth tour of some of the most useful methods in Machine Learning— classifying, regression, a bit of clustering. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas MŸller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.
The Hundred Page Machine Learning Book
Concise and to the point — the book can be read during a week. During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.
Hands-On Machine Learning with Scikit-Learn, Keras and Tensor Flow: Concepts, Tools and Techniques to Build Intelligent Systems (Colour Edition)
This is the second edition of the book with color and more emphasis on Tensorflow.
By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—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.
Make Your Own Neural Network by Tariq Rashid
The book provides you a step-by-step gentle journey through the mathematics of neural networks, and making your own using the Python computer language. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work.
You won’t need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. You’ll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks.
Python Machine Learning, Second Edition
This book can be a bit difficult to digest for absolute beginner but once you understand the basic concepts, then you’ll enjoy this book. It provides a practical approach to key frameworks in data science, machine learning, and deep learning Use the most powerful Python libraries to implement machine learning and deep learning