It’s a tedious task to have to write code and prepare a machine for every possible scenario in a situation. That’s why machine learning is such a life saver. If you’re unsure what it is, here’s the concept in a nutshell. 

Machine learning is an application of artificial intelligence that gives systems the ability to learn from experiences. This means, you don’t have to prepare it for every variable in the simulation. The machine will end up teaching itself. 

In today’s world of bots and interactive assistants, this is an incredibly useful area of interest. So now might be a good time to learn a little something about it. And to help you do precisely that, we’ve gathered a list of the best machine learning books put together for enthusiasts of all kinds. 

Best Machine Learning Books

Machine learning can be complicated, to say the least. It can also be crucial for a good number of today’s professions. That’s why learning about it from the experts can come in handy. Below are the 6 best machine learning books, and what knowledge you can expect to gain from each.

Machine Learning For Absolute Beginners: A Plain English Introduction 

Machine Learning For Absolute Beginners: A Plain English Introduction

This book is an excellent place for beginners. It comes with a bunch of important theories that you need to know before you take it to the next level. You will also learn some much-needed statistical principles that will help you move forward. This is an introductory book that does not assume any knowledge on your part. 

You will start learning about downloading free datasets, tools and machine-learning libraries that you’ll need going forward. There’s also chapters on how to scrub data, regression analysis, clustering and the basics of neural networks. You will also learn about bias or variance, decision trees, etc. It comes in multiple formats and is very affordable.

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Machine Learning (in Python and R) For Dummies 

Machine Learning (in Python and R) For Dummies

This one is also a great starter book for those who’re just beginning to dabble their feet in machine learning. Whether you want to understand search results on the web or real-time ads or any version of spam filters, you will need to understand machine learning to a certain extent. This book makes exactly that possible. 

This is for you to educate yourself in essential languages like Python and R that will allow you to understand data analysis and pattern-oriented tasks. It comes in multiple formats and is very reasonably priced. 

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Deep Learning 

Deep Learning

This is for expert-level learning. You will gain a deeper understanding of algorithms and how to tackle problems in machine learning. This is more of a reference book for when you read scientific papers, which are more useful at an expert level. You will learn about almost all kinds of problem-solving techniques at this level. 

This is to help to allow machines to learn and understand in a proper hierarchy. Systems often gather information but are unable to organize it without a guide. This book gives you the key to all such problems that a system could possibly face. It comes with a graph of all hierarchies which helps you understand and prepare your system to deal with the many layers of automation.

You will gain a better understanding of mathematics and the concepts of linear algebra, probability and information theory. You will also learn about numerical computation and the fundamentals of machine learning. This is a great book for undergraduate or graduate students who want to improve their understanding of the subject before entering the industry. It comes in multiple formats. It’s slightly more expensive than the other books for expert reading but it’s the L’Oréal of expert machine learning books—totally worth it.

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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

This is a book for programmers who know almost nothing about machine learning. It has efficient tools that allow you to implement programs by learning from data. The book is more on the practical side of implementing machine learning. 

It uses examples from minimal theory and two Python frameworks: Scikit-Learn and TensorFlow. It is written for those who want to understand the concepts and gain tools that will help build intelligent systems. You will learn about a whole host of techniques from linear regression to deep neural networks. Each chapter also has exercises that will help you test your level of understanding. 

You will find several training models, vector machines and decision trees, etc. that will help you explore machine learning. You will learn to build and explore neural net architectures along with deep reinforcement learning. It comes in multiple formats and is cheaper than the others in this category. 

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Introduction to Machine Learning with Python: A Guide for Data Scientists 

Introduction to Machine Learning with Python: A Guide for Data Scientists

This is another gem that will shine on a beginner’s bookrack. This is the one to buy if you’re looking to learn about the commercial applications of machine learning. It will also help with research projects and help you with large-scale projects in huge companies. 

You will learn several practical ways of building your own solutions with the available data. You will be able to create applications that will successfully demonstrate machine learning with Python. There is very little mathematics in this book and it’s mostly about staying on the practical side of things.   

You will be able to familiarize yourself with the fundamentals of machine learning in terms of both concepts and applications. You will know the advantages and disadvantages of commonly-used algorithms. You will be able to represent the data processed by machine learning. You will gain insight into advanced models for evaluation and parameter tuning. After a thorough reading of this book you will be limited only by your imagination. It comes in multiple formats and is not too expensive for a book that offers as much as it does. 

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The Hundred-Page Machine Learning Book

The Hundred-Page Machine Learning Book

This is a great book for beginners and experts to brush up to do a touch-up of fundamentals. Whether you’re a software engineer or just someone who is curious about machine learning, you can pick this copy up knowing you’ll walk away with a good deal of information and understanding of the subject. 

As the title suggests, in just a hundred pages, you will be able to learn about support vector machines, cluster analysis, neural networks and dimensionality reduction. It also has Q&As and further reading suggestions that will help you take your learning to the next level organically. It comes in multiple formats and is quite affordable. 

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In Conclusion: Best Machine Learning Books

Today, machine learning has become a crucial part of functions in many fields. So much so that there are fears of automation putting human beings out of work. We’ve all heard the conspiracies (hello, Skynet).   

But despite the threat, the subject itself is so relevant and captivating that there is actually a large cache of books on the internet – free and paid – for the different levels of expertise – beginner, intermediate and expert – that you seek. After reading one (or many) of these books on machine learning, you can also continue your knowledge with one of the courses found in our best machine learning courses guide.

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