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Best Machine Learning Books That You Need

Our list of some of the best Machine Learning books & series in recent years. Get inspired by one or more of the following books.

1. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems (2017)

 Best Machine Learning Books That You Need.Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting…
Author(s): Aurélien Géron

2. The Hundred-Page Machine Learning Book (2019)

 Best Machine Learning Books That You Needto avoid counterfeit, make sure that the book . Avoid third-party sellers. , Research Director at Google, co-author of , the most popular AI textbook in the world: “Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing the topics — both theory and practice — that will be useful to practitioners, and for the reader who understands that this is the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field.” , Senior AI Engineer, author of the bestseller : “The breadth of topics…
Author(s): Andriy Burkov

3. Machine Learning: An Applied Mathematics Introduction (2019)

 Best Machine Learning Books That You NeedA fully self-contained introduction to machine learning. All that the reader requires is an understanding of the basics of matrix algebra and calculus. Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the most important techniques. Chapter list: An appendix contains links to data used in the book, and more.The book includes many real-world examples from a variety of fields including Paul Wilmott brings three decades of experience in education, and his inimitable style, to this, the hottest of…
Author(s): Paul Wilmott

4. Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition (2017)

 Best Machine Learning Books That You NeedMachine learning is eating the software world, and now deep learning is extending machine learning. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschka’s bestselling book, Python Machine Learning. Thoroughly updated using the latest Python open source libraries, this book offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis.Fully extended and modernized, Python Machine Learning Second Edition now includes the popular TensorFlow deep learning library. The…
Author(s): Sebastian Raschka, Vahid Mirjalili

5. Machine Learning For Absolute Beginners: A Plain English Introduction (Machine Learning For Beginners) (2018)

 Best Machine Learning Books That You NeedReady to crank up a virtual server and smash through petabytes of data? Want to add ‘Machine Learning’ to your LinkedIn profile?Well, hold on there…Before you embark on your epic journey into the world of machine learning, there is some theory and statistical principles to march through first. But rather than spend $30-$50 USD on a dense long textbook, you may want to read this book first. As a clear and concise alternative to a textbook, this book provides a practical and high-level introduction to the practical components and statistical concepts found in machine learning. Machine Learning for Absolute Beginners Second…
Author(s): Oliver Theobald

6. Introduction to Machine Learning with Python: A Guide for Data Scientists (2016)

 Best Machine Learning Books That You NeedMachine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using…
Author(s): Andreas C. Müller, Sarah Guido

7. Machine Learning: The Absolute Complete Beginner’s Guide to Learn and Understand Machine Learning From Beginners, Intermediate, Advanced, To Expert Concepts (2019)

 Best Machine Learning Books That You Need★★Buy the Paperback Version of this Book and get the Kindle Book version for FREE ★★Machine Learning: The Complete Beginner’s Guide to learn and Understand Machine Learning, gives you insights into what machine learning entails and how it can impact the way you can weaponize data to gain incredible insights. Your information is pretty much as good as what you are doing with it and the way you manage it.In this book, you find out types of machine learning techniques, models, and algorithms that can help achieve results for your company. This data helps each business and…
Author(s): Steven Samelson

8. Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition (2019)

 Best Machine Learning Books That You NeedMachine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings. This new 3rd edition updates the classic R data…
Author(s): Brett Lantz

9. Mathematics for Machine Learning (2020)

 Best Machine Learning Books That You NeedThe fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression,…
Author(s): Marc Peter Deisenroth, A. Aldo Faisal, et al.

10. Machine Learning: A Quantitative Approach (2018)

 Best Machine Learning Books That You Need:     Machine learning is a newly-reinvigorated field. It promises to foster many technological advances that may improve the quality of our life significantly, from the use of latest, popular, high-gear gadgets such as smart phones, home devices, TVs, game consoles and even self-driving cars, and so on, to even more fun social and shopping experiences. Of course, for all of us in the circles of high education, academic research and various industrial fields, it offers more challenges and more opportunities.  Whether you are a CS student taking a machine learning class or…
Author(s): Henry H Liu

11. Machine Learning with Python: The Ultimate Beginners Guide to Learn Machine Learning with Python Step by Step (2019)

 Best Machine Learning Books That You NeedWe live in a world of data deluge where gigabytes of data are generated daily. It is possible that this data might not be very useful for our daily applications. Major setbacks in the use of such data may be due to the presence of loopholes in data links previously generated or the data might be too vast for the limited human mind. Machine learning in this book presents some of the solutions to the problems above. Being an introductory guide, expect to learn the various basics involved in Machine Learning and Python. This book provides an insight into the new world of big data, then…
Author(s): Mr Ethan Williams

12. Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning (2018)

 Best Machine Learning Books That You NeedThis practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics.Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help…
Author(s): Chris Albon

13. MACHINE LEARNING WITH PYTHON: An introduction to Data Science with useful concepts and examples, step by step, learning to use Python (2 BOOKS IN 1, FOR ABSOLUTE BEGINNERS AND NOT) (2019)

 Best Machine Learning Books That You NeedMachine Learning is a branch of AI that applied algorithms to learn from data and create predictions – this is important in predicting the world around us.Today, ML algorithms accomplish tasks that until recently only expert humans could perform and, as machines get ever more complex and perform more and more tasks to free up our time, so it is that new ideas are developed to help us continually improve their speed and abilities.Programmers who know close to nothing about this technology, now, can use simple, efficient tools to implement programs capable of learning from data.Python is a popular and open-source programming…

14. Machine Learning (2017)

 Best Machine Learning Books That You NeedPrinted in Asia – Carries Same Contents as of US edition – Opt Expedited Shipping for 3 to 4 day delivery -…
Author(s): Tom M Mitchell

15. Machine Learning Pocket Reference: Working with Structured Data in Python (2019)

 Best Machine Learning Books That You NeedWith detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project.Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You’ll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other…
Author(s): Matt Harrison

Best Machine Learning Books That You Need

We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Genesis and download some machine learning books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.

Detecting regime change in computational finance: data science, machine learning and algorithmic trading

Author(s): Chen, Jun; Tsang, Edward
ID: 2784924, Publisher: CRC Press, Year: 2021, Size: 15 Mb, Format: pdf

Advanced machine learning technologies and applications. AMLTA 2020

Author(s): Hassanien A.E (ed.)
ID: 2791382, Publisher: Springer, Year: 2021, Size: 10 Mb, Format: pdf

Computational Intelligence and Machine Learning: Proceedings of the 7th International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2019)

Author(s): Jyotsna Kumar Mandal, Imon Mukherjee, Sambit Bakshi, Sanjay Chatterji, Pankaj K. Sa
ID: 2826461, Publisher: Springer Singapore, Year: 2021, Size: 7 Mb, Format: pdf

Please note that this booklist is not absolute. Some books are truly record-breakers according to Washington Post, others are drafted by unknown authors. On top of that, you can always find additional tutorials and courses on Coursera, Udemy or edX, for example. Are there any other relevant resources you could recommend? Drop a comment if you have any feedback on the list.

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Comments: 1
  1. johny vinho

    I prefer Machine Learning: An Applied Mathematics Introduction for its behind scene approach. Although you need to have some calculus knowledge. It really helped later understand the practical approach.

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