Machine Learning Books to Read
Everyone learns in their own manner, and for some people, reading may be a terrific method to brush up on a current ability or learn something completely new. There are some excellent books on the subject of machine learning (ML) if you’re interested. Which one is best for you is determined on how much knowledge you already have. If you’re new to machine learning, there are a number of excellent books available. A number of great digital machine learning ebooks are now accessible.
There is likely to be a book that is appropriate for you, no matter where you are on your machine learning journey. Here are a few of our personal favourites:
1. The One-Hundred-Page Machine Learning Books :
This book offers all you need to know about machine learning, according to Analytics Vidhya, who characterises it as “beautifully written.” It not only introduces readers to the concept of machine learning, but also delves into the many forms of machine learning, including supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Basic techniques, advanced practises, classifications, learning algorithm anatomies, and other useful hints are also included.
2. Machine Learning: The Next Generation of Artificial Intelligence
WhatPixel suggests this book, authored by a well-known academic, if you’re seeking for a more recent release (who is also highly skilled in machine learning). Pattern recognition, neural networks, deep learning, and learning clusters are just a few of the techniques and topics covered in this book.
3. Statistical Learnings Elements:
Members of the Hackernoon community are said to favour The Elements of Statistical Learning. With mathematics and statistics at the heart of machine learning, this book is a must-read for anybody interested in breaking into the field. Support vector machines, neural networks, classification trees, and boosting are just a few of the subjects discussed.
4. Using Machine Learning to Work:
Tableau, a data visualisation and reporting business, recommends this book to anybody new to machine learning who wants to learn everything there is to know. This book teaches readers the essentials. It includes topics such as dataset splitting, association analysis, the Apriori method, and a number of machine learning tools.
5. Machine Learning: A Beginner’s Guide to Technical Machine Learning
This book, which Solutions Review recommends as a top selection for novices, illustrates how crucial machine learning is today and the technologies necessary to make it work. Readers will learn not just the fundamental principles that underpin machine learning, but also advanced topics such as programming languages (such as Python), logistic regression, decision trees, and much more.
6. Machine Learning Yearning:
This book takes a strategic corporate approach to machine learning, covering everything from the data science process through data visualisation. Readers will also become familiar with some of the main terminology they may see frequently in the industry. This book is especially useful for people interested in a career in marketing or retail, as it introduces readers to industry-specific machine learning applications.
7. Learning from Data:
This book delves into approaches used in a variety of fields, including finance, engineering, business, and science. If you’re searching for an online solution, this is a terrific option because readers have access to online chapters that are updated on a regular basis to reflect current industry trends.
8. A Plain English Introduction to Machine Learning for Absolute Beginners:
When you have no prior experience with machine learning, it might be scary. For a newcomer, the ideas and vocabulary may be quite difficult to grasp, nearly enough to put some individuals off. With its straightforward approach, this book seeks to alter that. Visual examples and simple explanations help readers grasp the fundamentals of machine learning. Because this book is aimed solely at novices, it is not advised for individuals who are farther along in their education.
If you want to pursue a career in machine learning, you should study as much as you can about this complicated topic. Books may be a terrific method to learn new topics, from the basics to advanced ideas, but they may not be practical as a primary source. Enrolling in a Machine Learning course that gives complete coverage of the discipline through a blended learning strategy is one of the finest methods to obtain formal training in ML. Students who participate in Simplilearn’s online learning programme may ask questions of professional teachers and receive feedback, as well as practise what they’ve learned through practical hands-on projects.