Best Machine Learning Books for Intermediates/Experts

6. Pattern Recognition and Machine Learning (1st Edition)

In case you want to dive deep into the mysterious world of Pattern Recognition and Machine Learning, then this is the correct book for you! In fact, this is the first book that presents the Bayesian viewpoint on pattern recognition. So while this book deals with tough topics that require at least some knowledge of multivariate calculus, basic linear algebra, and data science, this is also the best book to hammer Pattern Recognition into your brain!!! 

Pattern Recognition and Machine Learning have increasing difficulty level chapters on probability and machine learning based on patterns in datasets. So this book starts from the general introduction in Pattern Recognition using live examples to get the point across.

Buy Pattern Recognition and Machine Learning Book 

7. Fundamentals of Machine Learning for Predictive Data Analytics

If you have understood Machine Learning basics and now want to get into Predictive Data Analytics, then this is the book for you!!! Machine Learning can be used to create predictive models by extracting patterns from large datasets. And this application of ML using Predictive Data Analytics is analyzed in detail in this book using both theoretical concepts and practical applications. Even though the name “Fundamentals of Machine Learning for Predictive Data Analytics” is a mouthful, still this book will describe the Predictive Data Analytics trajectory in detail: from data to insight to a decision. 

It also describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning, each with a nontechnical conceptual explanation followed by mathematical models and algorithms illustrated by detailed work examples. 

Buy Fundamentals of Machine Learning for Predictive Data Analytics Book 

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

If you are at the intermediate or expert level in ML and want a “back to the basics” approach, then this book is the way to go! It does full justice to the incredible complexity and richness of Machine Learning without losing sight of its unifying principles (And that’s a feat!). Machine Learning: The Art and Science of Algorithms has various case studies with increasing complexity and many examples and illustrations as well (To make sure it’s not boring!) 

Also, a wide range of logical, geometric, and statistical models are covered in the book along with complex and new topics like matrix factorization and ROC analysis. 

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

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

Do you want to understand and then harness the power behind search rankings, product recommendations, social bookmarking or even online matchmaking!!! If you do, then congratulations, you have chosen the correct book. This book demonstrates how you can build various applications for Web 2.0 to mine the enormous amount of data that is created by approximately 3 Billion people on the Internet. 

Programming Collective Intelligence handles this using Machine Learning and helps you draw conclusions about user experience, marketing, personal tastes, and human behavior in general. All of the Machine Learning algorithms in this book are described with code that can be used anywhere from your website, blog, Wiki, or even a specialized application. 

Buy Programming Collective Intelligence Book

10. Deep Learning (Adaptive Computation and ML Series)

This book is an upgraded version of machine learning as it provides a proper understanding of a lot of data present in the book. If someone wants to gain appropriate knowledge of machine learning then they must go through this book as it is also known as the Bible of Deep Learning. The book contains technical topics, deep generative models, along with mathematics. A few more important topics covered in this book are:

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

Buy Deep Learning (Adaptive Computation and ML Series)

Alan Turing stated, “What we want is a machine that can learn from experience.” And this concept is a reality today in the form of Machine Learning! Generally speaking, Machine Learning involves studying computer algorithms and statistical models for a specific task using patterns and inference instead of explicit instructions. And there is no doubt that Machine Learning is an insanely popular career choice today. 

According to many sources, Machine Learning Engineer is The Best Job with a 344% growth and an average base salary of $146,085 per year. Keeping this in mind, if you want to learn Machine Learning, there are many books available in the market (for programmers at all stages of learning). In this article, we have compiled the best machine learning books, both for rank amateurs and technical whiz kids!!! Each of these books is extremely popular so it is up to you to choose the ones you like according to your learning sensibilities. So without further ado, let’s see them!