Machine Learning is a trending branch of Computer Science in which a lot of people are seeking their careers. It is related to Artificial Intelligence, which deals with providing the required modifications and development to the system through which it gets the ability to access the data and use it to learn for themselves.

With the advancement in technology and computer-based careers and jobs, the field of computer science is doing a lot of progress and therefore the vast area of study is branching out in order to provide the students with specific areas for studying and to seek their careers in.

If you are interested in learning the concept of Machine learning you may want to read some books written on the subject. But the kind of book would totally depend on your level of understanding of the topic. Therefore, for your convenience, we have categorized the machine learning books into three parts, namely for beginners, for intermediates and for experts.

From these categories, you can choose the one that suits your understanding of the subject. Each book listed in these categories is selected on the basis of public review and their popularity among readers. Follow the list given below to know some best machine learning books.

Best Machine Learning Books for Beginners:

The books that are included in this category are for the students who are just thinking about stepping in the field. These books will explain to you the concepts associated with the subject from the very beginning and you will not be required to have any prior knowledge on the matter.

1. Introduction to Machine Learning with Python

Introduction to Machine Learning with Python

This book is best to start if you are learning the subject on an introductory level. Introduction to Machine Learning with Python is written by Andreas C Muller and Sarah Guido. The book will introduce you to all the fundamental concepts that are associated with the subject.

It will provide you with a gentle introduction of Machine Learning meanwhile creating a base of understanding. Introduction to Machine Learning with Python is an entry-level book that will guide you through in the subject while providing you significant knowledge about Python.

2. Machine Learning For Absolute Beginners: A Plain English Introduction (2nd Edition)

Machine Learning For Absolute Beginners: A Plain English Introduction

If you are passionate about studying Machine Learning but are unaware of where to start? Then this book is your calling. Machine Learning for Absolute Beginners is, as the name suggests, for the students who are just stepping into the field. It will introduce you with various statistical and practical methods used in the process of understanding the subject.

The book is written by Oliver Theobald. It uses a special practical approach that will help the students in understanding the application of machine learning.

3. Machine Learning (in Python and R) For Dummies (1st Edition)

Machine Learning (in Python and R) For Dummies

Machine Learning for Dummies is authored by John Paul Mueller and Luca Massaron. The book is specially designed for people who not aware of the concepts of machine learning and do not know how to start. Machine Learning for Dummies will explain everything to you in great detail and will provide you with a fundamental base on the subject.

The book is written in such a way that individuals not having any prior knowledge of Machine Learning will be able to understand it easily. Along with this, the book will also help you develop an understanding of certain languages such as python and R.

4. Machine Learning for Hackers: Case Studies and Algorithms to Get You Started (1st Edition)

Machine Learning for Hackers: Case Studies and Algorithms to Get You Started

Machine Learning for Hackers is written by Drew Conway & John Myles. The book is designed for students who are interested in the data crunching. It has an interesting approach to explaining the concepts related to Machine Learning. Instead of using heavy mathematical calculations the book has involved several case studies that make the process less boring.

In each chapter, you will find a different area of focus. The chapters are divided into classifications, optimization, predictions, recommendations, etc. In the R programming language, you will learn a simple machine learning algorithm.

5. Machine Learning: The New AI (The MIT Press Essential Knowledge Series)

Machine Learning: The New AI

Machine Learning: The New AI is written by Ethem Alpaydin. The main focus of the book is towards providing beginners with basic knowledge about various concepts concerned with the subject such as data science, reinforcement learning, machine learning algorithm for pattern recognition and artificial neural networks, also, ethical and legal implications of data science for privacy and security.

Apart from this, you will also find pretty valuable information in this book about the application, learning algorithm, etc.

Best Machine Learning Books for Intermediates

Intermediates, who have some pretty basic knowledge on the subject and are seeking to learn some more in order to gain expertise should refer to the books given below. Having some fundamental knowledge about Machine learning will help before reading the following books.

1. Python Machine Learning

Python Machine Learning

The author of Python Machine Learning is Sebastian Raschka and Vahid Mirijalili. The book is written for students who understand the fundamental language associated with the subject of machine learning. Python Machine Learning uses a practical approach to explaining the topics. The book is equipped with a lot of examples of code for the students to learn.

Initially, you will find some basic knowledge in the book but as the book proceeds, you will get more deep and advanced knowledge on the subject. The language of the book is understandable by the general audience that is why anyone could read it, but to be able to understand it you must know some fundamentals of machine learning.

2. Hands-on Machine Learning with Scikit-Learn and Tensor-flow

Hands-on Machine Learning with Scikit-Learn and Tensor-flow

Hands-on Machine Learning with Scikit-learn and Tensor-flow is written by Aurelien Geron. It is considered one of the best machine learning books to refer to at an intermediate level. Along with providing you with all the necessary knowledge about Machine Learning and its basic, it gently proceeds towards deep learning.

The author of this book has brilliantly organized this book in a manner in which people at any level will be able to understand it. But it is best to start this book at mid-level it is written in such a way that it will facilitate learning at an intermediate level perfectly.

3. Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning is authored by Christopher M. Bishop. The book is great for students who are interested in the pattern recognition aspect of machine learning. Interestingly enough, this is the first-ever book that will provide you with a Bayesian viewpoint on pattern recognition.

Before starting this book make sure you have some basic knowledge about data science, multivariate calculus, and linear algebra. It will really help you understand the book completely if you are cleared of these concepts already. Pattern recognition itself is a pretty complicated subject to understand so this book will first give you all the general knowledge then dive into some complexities.

4. Fundamentals of Machine Learning for Predictive Data Analytics

Fundamentals of Machine Learning for Predictive Data Analytics

Another one on the list is the Fundamentals of Machine Learning for predictive data analytics which is written by John D. Kelleher. If you want to get into the predictive data analysis aspects of machine learning then this is the book for you. Before you start this book make sure you have some basic knowledge about machine learning.

Fundamentals of machine learning for predictive data analysis uses different approaches for explaining predictive analysis. For example, you will find probability-based learning, information-based learning, similarity-based learning and error-based learning in the book. Along with this, with each approach, you will get a nontechnical explanation of the concepts that use mathematical models and algorithms.

5. Machine Learning: The Art and Science of Algorithms that Make Sense of Data (1st Edition)

Machine Learning: The Art and Science of Algorithms that Make Sense of Data

Author Peter Flach, in his book, Machine learning: The art and science of algorithms that make sense of data has brilliantly done justice to the complexities and richness of machine learning. If you are intermediate who is already familiar with what machine learning is and wants to explore more in this field then this book will provide you with numerous case studies, mathematical models, algorithm illustrations, etc.

Along with this, the book has an interesting approach to machine learning and also introduce you with new topics such as matrix factorization and ROC analysis.

Best Books of Machine Learning for Experts

At expert level, you are pretty much aware of all the aspects associated with machine learning, but you know what they say, learning is an endless process and one will never get too much knowledge about anything. So when you are an expert, you may want to read the books that already starts at an advanced level. So please refer to the following books of machine learning at an expert level.

1. Deep Learning with Python

Deep Learning with Python

Deep learning with Python is written by Francois Chollet, who is a creator of Keras, one of the renowned machine learning libraries in Python. The book is totally focused on deep learning and uses practical approached to help the experts trying to get more knowledge on the subject.

It is equipped with some pieces of code that are ready to use by the readers. Along with this, you will also find some general tips and useful examples that will help you in gaining a grip on the subject.

2. Programming Collective Intelligence: Building Smart Web 2.0 Applications (1st Edition)

Programming Collective Intelligence: best machine learning books

The author of the book Programming collective intelligence: building smart web 2.0 applications is Toby Segaran. The book is written at an expert level and only the individuals having the fundamental knowledge on the subject should refer to it, as it uses an advanced level approach.

The book will give you all the required knowledge of social bookmarking, product recommendations, online matchmaking, search rankings, etc. In general, this book will help you draw conclusions about the various aspects associated with remarketing such as user experience, marketing, human behavior, marketing, etc.

Conclusions

Machine learning is a complicated subject and could be hard to understand sometimes but not if you have the right book for you. Students having different levels of understanding on the subject may need a different book for mastering it and that is why for your convenience we have divided the whole list into three categories from which you can choose the book that suits you the best.

The books that are mentioned below are all one of the best books written on the subject. They are selected after careful evaluation and estimating different factors that contribute to making a book great.

Do let us know in the comment section how you liked this article, also if you have any queries we will be happy to help you with that.