machine learning books

8 Best Books in Machine Learning to Read in 2021

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Last Updated on May 9, 2021

By the way, we all know that in these few years, machine learning technology has emerged very fast. Many businesses, scientists, or industries have shown their interest in the field of machine learning. That’s why today I will tell you about some best books in machine learning that an ML beginner or an engineer must read.

All of you must have agreed that the mind is at a different stage than reading books. Our mind explores a lot of new things by reading books. Because Reading is Learning. Having a self-learner tag brings a lot of fun.

Read this post closely otherwise you are gonna miss the main points(lists of books, why it will be good for us? what is so special about these books?) But before jumping into that section, let us know what is the best definition of machine learning?

Machine Learning

Machine Learning is the subset of artificial intelligence. It refers to a system that has the ability to learn itself from the data and able to make accurate predictions without being explicitly programmed.

It is an area of computational science that aims to create a technology that has the capacity to learn, the ability to make decisions, the ability to inquire. Just like humans do.

Best Books in Machine Learning to Read

1. Hands-on ML with Scikit-Learn, Keras & TensorFlow

Hands-on MLwith Scikit-Learn, Keras & TensorFlow
  • Author – Aurélien Géron
  • Edition – Second Edition
  • Publisher – O’Reilly Media, Inc.

This Book is the best practical introduction to machine learning and will focus on implementing ML programs using the library Scikit-Learn, Keras & TensorFlow2.

In this second edition book, some new topics have been included, which were not in the first edition book. Those topics are the K-Means and Gaussian mixes in the chapter Unsupervised Learning Techniques. Well, this book assumes that you know close to nothing about machine learning. You will get here a concept, tools to implement a machine learning algorithm.

Important Topics Covered Here :-

This book would be best for you because it mixes theories with practice and lots of tremendous projects. Along with these things, there are also such amazing topics that will make you enjoy while reading, because it has 250 extra pages that 1st Edition.

  • Biological Neurons
  • Supervised and Unsupervised Learning Techniques
  • Neural Network and Deep Learning
  • Deep CV using CNN
  • Algorithm Fundamentals
  • End-To-End Projects

You can buy this book here.

2. Mathematics for Machine Learning

Mathematics For Machine Learning
  • Author – Marc Peter Deisenroth
  • Edition – First Edition
  • Publisher – Cambridge University Press

If you are learning machine learning, then you must have known how important mathematics is in machine learning. There are some books that will explain the concepts of machine learning very well, but what about the mathematics that is behind that ML Concepts. That’s why this book will help you a lot here.

Well, The purpose of this book is not to cover advanced machine learning techniques. Rather, it is to provide necessary mathematical skills. So, the beginner could get it easily. It will be the best book for you if you are looking to study the math of machine learning.

Important Topics Covered Here:-

Here this book will teach you two main fundamentals, i.e. 1.) Mathematical Foundation. 2.) Example of machine learning algorithms that use mathematical foundations.

  • All Mathematical Topics with Exercises
  • Continuous Optimization
  • Linear Regression

You can buy this book here.

3. Python Machine Learning By Example

Python Machine Learning By Example
  • Author – Yuxi (Hayden) Liu
  • Edition – Third Edition
  • Publisher – Packt Publishing

Practice matters the most in any study, whether you are studying machine learning or anything else. And this machine learning book would be perfectly fit for you, if you are willing to solve the complex problems faced by data scientists, using machine learning algorithms.

This ML Python book will explain you the concepts of ML and data science in depth. But before diving into this book, I would suggest you to get acquainted with the basics of statistical concepts. Along with the concepts, there are a bunch of examples (projects) here that you can practice.

Important Topics Covered Here:-

There are amazing topics covered here, but before that, I would say if you are highly passionate about machine learning and want to start working on machine learning assignments, this book is for you.

  • Building a Movie Recommendation Engine with Naive Bayes
  • Recognizing Faces with Support Vector Machine
  • Predicting Stock Prices with Artificial Neural Networks
  • Making Decisions in Complex Environments with Reinforcement Learning

You can buy this book here.

4. Introduction to Machine Learning with Python

Introduction to Machine Learning with Python
  • Author – Andreas C. Müller, Sarah Guido
  • Edition – First Edition
  • Publisher – O’Reilly Media, Inc.

As a beginner in machine learning, this book will help you a lot to create a successful machine learning applications with python and scikit-learn library. If you are willing to become a data scientist by profession, then it will be your ideal book to start your machine learning journey.

With this book, you will get to know all those fundamental concepts and applications that will help you to boost your knowledge and experience in machine learning. Because it has covered all the topics in a simpler way.

Important Topics Covered Here:-

Before reading this book, you should be familiar with NumPy and Matplotlib libraray, because it will help you to learn even better.

  • Concept of pipelines for chaining models and encapsulating your workflow
  • Advanced methods for model evaluation and parameter tuning
  • Advantages and shortcomings of widely used machine learning algorithms
  • Representing Data and Engineering Features

You can buy this book here.

5. The Hundred-Page Machine Learning Book

The Hundred-Page Machine Learning Book
  • Author – Andriy Burkov
  • Edition – First Edition
  • Publisher – Andriy Burkov

The most important thing about this book is that it will explain you concepts of machine learning very well and that too within 100 pages(100+). Many editors have reviewed this book and said an excellent thought about this book. It will explain you all the complex topics even in a simple way.

After this book, you will be able to create such machine learning projects and yes, it will also help you for preparing an ML-based interview.

Important Topics Covered Here:-

  • Fundamental Algorithms
  • Neural Networks and Deep Learning
  • Advanced Practice
  • Anatomy of a Learning Algorithm
  • Unsupervised Learning

You can buy this book here.

6. Machine Learning For Absolute Beginners

Machine Learning for Absolute Beginners
  • Author – Oliver Theobald
  • Edition – Third Edition
  • Publisher – Independently published

This book will be very useful for ML beginners to learn machine learning concepts. To make it more readable, this book has provided clear explanations and visual examples of ML concepts and core algorithms.

Well, this book does not include everything to master machine learning. It is designed for readers taking their first steps in machine learning. But if you are absolute beginner in ML field, you must have this book.

Important Topics Covered Here:-

  • Machine Learning tools and libraries
  • Regression analysis
  • Decision Trees
  • Bias/Variance
  • Machine Learning models
  • k-Means Clustering to find new relationships

You can buy this book here.

7. Python for Data Analysis

python for data analysis
  • Author – Wes McKinney
  • Edition – Second Edition
  • Publisher – O’Reilly Media, Inc.

Well, the most important thing you have to do as a machine learning engineer is to analyze the data used in machine learning. Most of the time you spend manipulating data, processing it, cleaning and analyzing it then get ready to make ML model that gives an accurate prediction.

To do data analysis, you should have proper knowledge of Pandas, NumPy, Ipython, etc. If you want to get into data science or machine learning, you have to know how to manipulate data. For this, Python for Data Analysis book will be totally worth it for you.

Important Topics Covered Here:-

  • Essential Python Libraries
  • Mathematical and Statistical Methods
  • Summarizing and Computing Descriptive Statistics
  • Data Cleaning and Preparation
  • Advanced Pandas
  • Data Analysis Examples

You can buy this book here.

8. Deep Learning (Adaptive Computation and ML Series)

deep learning
  • Author – Ian Goodfellow, Yoshua Bengio, Aaron Courville
  • Edition –
  • Publisher – The MIT Press

As we all know, deep learning is a form (upgraded version) of machine learning and it enables computers to learn from experience and a lot of data. While practicing machine learning concepts, you will also need to have proper knowledge of deep learning concepts. Here, this book will help you a lot, because it is considered, the Bible of Deep Learning.

Three experts in the field of deep learning have introduced extremely technical topics, full of mathematics, and deep generative models in this book.

Important Topics Covered Here:-

  • Numerical Computation
  • Deep Feedforward Networks
  • Optimization for Training Deep Models
  • Practical Methodology
  • Deep Learning Research

You can buy this book here.

That’s all here. These are the books that are the most recommended and best books in machine learning. According to your topics and field, you can choose any of these books. I hope you liked the article, if you have any questions please let me know in the comment section.

Thank You

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