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9 Free Data Science Books to Read in 2021

Overview

  • Here are 9 free data science books to get started and upgrade yourself on various fronts
  • By no means is this an exhaustive list. Feel free to add more free data science books in the comments below

 

Introduction

“Data indeed is the new oil”

When I heard this for the first time many years ago, I mocked and ignored the statement. And, I am pretty sure many people like me are now thinking about how accurate this statement was.

Currently, Data science has taken over all the industries without leaving any stones unturned. Every firm is trying to leverage a panoply of data at each and every step of its operations to obtain ultimate efficiency. It only makes sense for people to familiarize themselves with at least basic algorithms and tools to analyze the data in their respective domains to better understand the trends and in turn, make better decisions.

And if you are already in your data science journey, you must have realized how important it is to upgrade yourself and practically implement complex algorithms for better results.

But like every time, you always wonder where to begin. That’s where I come to your rescue. In this article I am sharing 9 of the top free Data Science Books people must add to their list by the end of 2020.

 

 

1. Statistical Learning with Sparsity: The Lasso and Generalizations by Trevor Hastie, Robert Tibshirani, Martin Wainwright

The book includes all the major branches of statistical learning. For each topic, the authors first give a concise introduction of the basic problem, evaluate conventional methods, pointing out their deficiencies, and then introduce a method based on sparsity.

free data science books - statistical learning with sparsity

It always first discusses regularized models based on equations, followed by example applications, before ending with a bibliography section detailing the historical development of the given method.

You can download the book from here.

 

2. The Field Guide to Data Science by Booz Allen Hamilton

This book built by several hands by Booz Allen Hamilton employees introduces the theme of Data Science, presents the tools necessary to work with the area, and expands the background a little. It basically works as an introduction to the subject, but it is very well written, with infographics and illustrations that are especially creative. And there is a section that should be printed by everyone working in the field, a guide on how to choose the right technique for each piece of the problem.

free data science books -Booz Allen Field Guide to Data Science by [Booz Allen Hamilton]

You can download the book from here.

 

3. An Introduction to Statistical Learning by Gareth M. James, Daniela Witten, Trevor Hastie, Robert Tibshirani

An all-time classic. This book is recommended or referenced in most machine learning courses I’ve come across, it’s just that well written. It covers basic statistics as well as machine learning techniques.

ISLR

The awesome thing about this book is that each concept is explained with case studies in R. So once you have a handle on programming, you can always come back and try out each concept again. What better way to ingrain a concept than by practicing it multiple times?

You can download the book from here.

4. Convex Optimization 1st Edition by Stephen Boy

This is book Is not for beginners. The book introduces you to the concept of Convex Optimization which is used by almost all Machine Learning and Deep Learning Algorithms to reach the optimal parameters.

convex optimization

This is an appropriate book for someone looking to enter the world of machine learning through optimization. This is another approach apart from the journey via statistics.

You can download the book from here.

 

5. Data Mining and Analysis by Mohammed J. Zaki and Wagner Meira, Jr

The book provides a very good primer on the mathematical background for data mining and foundational statistical machine learning. This textbook provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification.

Data Mining and Analysis

The book lays the basic foundations of these tasks, and also covers cutting-edge topics such as kernel methods, high-dimensional data analysis, and complex graphs and networks.

You can download the book from here

 

6. Data Science for Business by Tom Fawcett and Foster Provost

The book introduces the fundamental principles of data science and walks you through the “data-analytic thinking” necessary for extracting useful knowledge and business value from the data you collect.

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

This book is recommended for beginners and intermediate professionals who would like to learn data analytics without the usage of mathematics.

You can download the book from here.

 

7. Deep Learning (Adaptive Computation and Machine Learning series) by IAN Goodfellow

If a man like Elon Musk says that this is the most comprehensive book on the topic, we don’t think you need to refer to any further sources for the topic.

Deep learning ian goodman

The topics in the book are comprehensive, it covers almost every edge related to deep learning, the authors made a good justification in covering some of the intricate topics that need close attention that isn’t so readily available on the internet.

You can download the book from here.

 

 

8. Deep Learning with Python by Francois Chollet

deep learning with python

Is there even an alternative way to learn Deep Learning than from learning through the book written by the Keras creator and Google AI Researcher Francois Chollet? The book deep dives into Deep Learning and teaches concepts by practically implementing in python in Python.

I also recommend following Francois on Twitter – there is a lot we can learn from him.

You can download the book from here.

 

9. Artificial Intelligence: Foundations of Computational Agents,  2nd Edition by David Poole,
Alan Mackworth

This is a book about the science of artificial intelligence (AI). It presents artificial intelligence as the study of the design of intelligent computational agents.

AIFCA cover

The book balances theory and experiment, showing how to link them intimately together. It develops the science of AI together with its engineering applications.

You can download the book from here.

 

End Notes

This article introduces you to free data science books that can help you kick start or upgrade your current position in your data science journey.

We recommend you to check out the list of books that can help you begin a career in Business analytics too-

Feel free to add other books in the comments that you think should have made the list.

 

 

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