Top 25 Essential Machine Learning Books For Beginners And Experienced Professionals - GUVI Blogs

• Read original article here

Find the top 22 Machine Learning Books for beginners and advanced Machine Learning Professionals here!

You get a free hour and decide to watch a movie. After a long search of half an hour, you end up switching off the TV and losing interest altogether! Does that happen with you? But not anymore! Because Netflix these days recommends the top movies and web series that are trending around you. Thanks to Machine Learning!

So, which web series is on your hit list today? Of course, you need not bookmark(as you would need to do this page) or save any titles again as they naturally come up on your recently watched list!

It is the tiniest wonder that Machine Learning facilitates. We have uncountable little wonder packs of Machine Learning, making lives easier. Whether in Virtual Assistants, self-driving cars, or Business intelligence, Machine Learning is hugely benefiting humankind.

Undoubtedly, the industry is looking for skilled Machine Learners who can add to their database of intellectual folks.

Indeed, the American worldwide employment website marked Machine Learning Engineers as one of the top jobs in the United States with regards to salary, growth of postings, and demand.

So, how are you planning to make your great beginning in the Machine Learning World? Books are the smartest option to turn to. Here are the top 22 Machine learning books for beginners that will guide you in and out of Machine Learning and related fields.

Let’s dig deep and find out the details of the top 5 Machine Learning books for beginners in this list:

But before we get started with that, here are some of our personal research resources for you: Check it out!

How to set up a Python environment for Machine Learning

A Plain English Introduction (Third Edition): 1 (Machine Learning with Python for Beginners)

A Newbie to Machine Learning? This book can be your best hideout. You can kickstart your Machine Learning journey here with no coding or mathematical background.  

Machine Learning concepts are very well defined and made sense in layman’s words with clear explanations, visual examples & various ML algorithms.

This book is designed for readers taking their first steps in machine learning. However, further learning will be required beyond this book to master machine learning.

To the point and short & sweet, this book can be read in a week! In this book learn everything that modern Machine Learning has to offer! The Hundred-Page Machine Learning Book appears to be a summary of decade years of experience of the authors of this book.

The best part of this book is the Companion wiki, which continuously updates & flares some book chapters with auxiliary information: Q&A, code snippets, further reading, tools, and other relevant resources.

After reading the top Machine learning books for beginners you may check this: Top 5 Luxury Jobs in Machine Learning 

Do you wish you could get familiar with the basic concepts and theories of Machine Learning? Then you would find no better book than Machine Learning for Dummies. The topics covered in the book go with the name of the book.

Additionally, the book focuses on the practical, real-world applications of machine learning. The book mentions how to train machines to find patterns and analyze results using Python and R code with an augmented advantage of illustrations on how ML facilitates email filters, fraud detection, internet ads, web searches, etc.

Though a rigorous and mathematically dense book, The Elements of Statistical Learning: Data Mining, Inference, and Prediction has a special emphasis on concepts rather than mathematics. With the liberal use of colour graphics, the book gives tons of examples to highlight the concepts. 

All three authors of the book are well-known Statistics Professors at Stanford University. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title.

In addition to having invented principal curves and surfaces, Author Hastie also wrote much of the statistical modelling software in S-PLUS. Author Tibshirani, on the other hand, proposed the Lasso and is co-author of the very successful book: An Introduction to the Bootstrap. Author Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

Little wonder then that this book appears in the top 5 of our top Machine Learning books recommended for good learning.

Included in our list of top 5 Machine learning books for beginners, the Learning from Data: A Short Course book is a short and crisp explanation of the Machine Learning concepts. This book can be a perfect choice for anyone who wants to get a comprehensive introduction to machine learning in less time.

It is a short course, not a hurried course. Comprehend the complex machine learning concepts with the easy explanations in this book.

Yes, let’s call it a wrap for now. The discussion on books especially on Top Machine Learning Book is never-ending. There are uncountable books coming up every year. So, we will keep updating the list here. For now, these are the books you can refer to.

Meanwhile, you master Machine Learning from the various Machine Learning Books for Beginners that we suggested, here’s a course in Data Science that you can take up or recommend to anyone who is interested. This IIT-M Certified Advanced Programming Professional and Data Science Course are for anyone who aspires to be a Data Science Professional. You may start learning from scratch with absolutely no programming knowledge & stand out as a Data Scientist in just 6 months.

Post your suggestions and queries about the top Machine Learning books for beginners in the comment section below.