50 Best Free Books for Machine Learning and Data Science

In this article, I am gonna mention the 50 Best Free Books for Machine Learning and Data Science. These books are released by Springer and cover various topics of machine learning and data science. So give your few minutes and find out the Best Free Books for Machine Learning and Data Science.

As we know that in data science and machine learning, knowledge of mathematics and statistics is crucial. So in this list, I have also added those books that will help you to learn mathematical and statistical concepts for data science. You will also find some advanced level books on machine learning and deep learning.

So without any further ado, let’s get started-

50 Best Free Books for Machine Learning and Data Science

For your convenience, I have created a table, so that you can easily find the book according to your need.

Note- If you are watching on Mobile Device, kindly scroll left to find the Download link.

S/N	Book Name	Author	Category	Download Link
1.	The Elements of Statistical Learning	Trevor Hastie, Robert Tibshirani, Jerome Friedman	Statistics	Download here
2.	A Beginner’s Guide to R	Alain Zuur, Elena N. Ieno, Erik Meesters	R Programming	Download here
3.	Introductory Time Series with R	Paul S.P. Cowpertwait, Andrew V. Metcalfe	R Programming	Download here
4.	Data Analysis	Siegmund Brandt	Data Analysis	Download here
5.	Introduction to Statistics and Data Analysis	Christian Heumann, Michael Schomaker, Shalabh	Data Analysis	Download here
6.	Principles of Data Mining	Max Bramer	Data Mining	Download here
7.	Data Mining	Charu C. Aggarwal	Data Mining	Download here
8.	Computer Vision	Richard Szeliski	Computer Vision	Download here
9.	Robotics, Vision, and Control	Peter Corke	Artificial Intelligence	Download here
10.	Statistical Analysis and Data Display	Richard M. Heiberger, Burt Holland	Statistics	Download here
11.	Statistics and Data Analysis for Financial Engineering	David Ruppert, David S. Matteson	Statistics	Download here
12.	Statistical Analysis of Clinical Data on a Pocket Calculator	Ton J. Cleophas, Aeilko H. Zwinderman	Statistics	Download here
13.	Stochastic Processes and Calculus	Uwe Hassler	Mathematics	Download here
14.	The Data Science Design Manual	Steven S. Skiena	Data Science	Download here
15.	An Introduction to Machine Learning	Miroslav Kubat	Machine Learning	Download here
16.	Guide to Discrete Mathematics	Gerard O’Regan	Mathematics	Download here
17.	Introduction to Time Series and Forecasting	Peter J. Brockwell, Richard A. Davis	Data Science	Download here
18.	Multivariate Calculus and Geometry	Seán Dineen	Mathematics	Download here
19.	Statistics and Analysis of Scientific Data	Massimiliano Bonamente	Statistics	Download here
20.	Linear Algebra Done Right	Sheldon Axler	Mathematics	Download here
21.	Modeling Computing Systems	Faron Moller, Georg Struth	Mathematics	Download here
22.	Search Methodologies	Edmund K. Burke, Graham Kendall	AI	Download here
23.	Linear Algebra	Jörg Liesen, Volker Mehrmann	Mathematics	Download here
24.	Understanding Analysis	Stephen Abbott	Data Analysis	Download here
25.	Understanding Statistics Using R	Randall Schumacker, Sara Tomek	R Programming	Download here
26.	An Introduction to Statistical Learning	Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani	Statistics	Download here
27.	Statistical Learning from a Regression Perspective	Richard A. Berk	Statistics	Download here
28.	Regression Modeling Strategies	Frank E. Harrell, Jr.	Machine Learning	Download here
29.	A Modern Introduction to Probability and Statistics	F.M. Dekking, C. Kraaikamp, H.P. Lopuhaä, L.E. Meester	Probability & Statistics	Download here
30.	The Python Workbook	Ben Stephenson	Python	Download here
31.	Machine Learning in Medicine — a Complete Overview	Ton J. Cleophas, Aeilko H. Zwinderman	Machine Learning	Download here
32.	Introduction to Data Science	Laura Igual, Santi Seguí	Data Science	Download here
33.	Applied Predictive Modeling	Max Kuhn, Kjell Johnson	Machine Learning	Download here
34.	Digital Image Processing	Wilhelm Burger, Mark J. Burge	Machine Learning	Download here
35.	Concise Guide to Databases	Peter Lake, Paul Crowther	Database Management	Download here
36.	Python For ArcGIS	Laura Tateosian	Python	Download here
37.	Bayesian Essentials with R	Jean-Michel Marin, Christian P. Robert	R Programming	Download here
38.	Introduction to Artificial Intelligence	Wolfgang Ertel	AI	Download here
39.	Introduction to Deep Learning	Sandro Skansi	Deep Learning	Download here
40.	Neural Networks and Deep Learning	Charu C. Aggarwal	Deep Learning	Download here
41.	Applied Linear Algebra	Peter J. Olver, Chehrzad Shakiban	Mathematics	Download here
42.	Linear Algebra and Analytic Geometry for Physical Sciences	Giovanni Landi, Alessandro Zampini	Mathematics	Download here
43.	Data Science and Predictive Analytics	Ivo D. Dinov	Data Science	Download here
44.	Analysis for Computer Scientists	Michael Oberguggenberger, Alexander Ostermann	Data Analysis	Download here
45.	Excel Data Analysis	Hector Guerrero	Data Analysis	Download here
46.	A Beginners Guide to Python 3 Programming	John Hunt	Python	Download here
47.	Advanced Guide to Python 3 Programming	John Hunt	Python	Download here
48.	Object-Oriented Analysis, Design, and Implementation	Brahma Dathan, Sarnath Ramnath	Data Analysis	Download here
49.	Applied Partial Differential Equations	J. David Logan	Mathematics	Download here
50.	Deep Learning	Genki Yagawa, Atsuya Oishi	Deep Learning	Download here

Here we go. So these are the 50 Best Free Books for Machine Learning and Data Science. I would suggest you bookmark this article for future referrals.

Conclusion

In this article, you have found 50 Best Free Books for Machine Learning and Data Science. I hope these books will help you to enhance your data science and machine learning skills. I will keep adding more free data science and machine learning books to this list. If you have any questions, feel free to ask me in the comment section.

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All the Best!

Happy Learning!

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