Free Computer Science Textbooks

Springer has put out a ton of awesome textbooks, and they made over
500 of them available for free download, including a couple dozen
tech ebooks!

An Introduction to Machine Learning, 2nd ed. 2017 by Miroslav
Kubat

Automata and Computability, 1997 by Dexter C. Kozen

Computational Geometry, 3rd ed. 2008 by Mark de Berg, Otfried
Cheong, Marc van Kreveld, Mark Overmars

Computer Vision, 2011 by Richard Szeliski

Concise Guide to Databases, 2013 by Peter Lake, Paul Crowther

Concise Guide to Software Engineering, 1st ed. 2017 by Gerard
O'Regan

Cryptography Made Simple, 1st ed. 2016 by Nigel Smart

Data Mining, 2015 by Charu C. Aggarwal

Data Structures and Algorithms with Python, 2015 by Kent D. Lee,
Steve Hubbard

Digital Image Processing, 2nd ed. 2016 by Wilhelm Burger, Mark J.
Burge

Eye Tracking Methodology, 3rd ed. 2017 by Andrew T. Duchowski

Foundations for Designing User-Centered Systems, 2014 by Frank E.
Ritter, Gordon D. Baxter, Elizabeth F. Churchill

Foundations of Programming Languages, 2nd ed. 2017 by Kent D.
Lee

Fundamentals of Business Process Management, 2013 by Marlon Dumas,
Marcello La Rosa, Jan Mendling, Hajo A. Reijers

Fundamentals of Multimedia, 2nd ed. 2014 by Ze-Nian Li, Mark S.
Drew, Jiangchuan Liu

Guide to Competitive Programming, 1st ed. 2017 by Antti
Laaksonen

Guide to Computer Network Security, 4th ed. 2017 by Joseph Migga
Kizza

Guide to Discrete Mathematics, 1st ed. 2016 by Gerard O'Regan

Introduction to Artificial Intelligence, 2nd ed. 2017 by Wolfgang
Ertel

Introduction to Data Science, 1st ed. 2017 by Laura Igual, Santi
Seguí

Introduction to Deep Learning, 1st ed. 2018 by Sandro Skansi

Introduction to Evolutionary Computing, 2nd ed. 2015 by A.E. Eiben,
J.E. Smith

LaTeX in 24 Hours, 1st ed. 2017 by Dilip Datta

Modelling Computing Systems, 2013 by Faron Moller, Georg
Struth

Object-Oriented Analysis, Design and Implementation, 2nd ed. 2015
by Brahma Dathan, Sarnath Ramnath

Principles of Data Mining, 3rd ed. 2016 by Max Bramer

Probability and Statistics for Computer Science, 1st ed. 2018 by
David Forsyth

Python Programming Fundamentals, 2nd ed. 2014 by Kent D. Lee

Recommender Systems, 1st ed. 2016 by Charu C. Aggarwal

The Algorithm Design Manual, 2nd ed. 2008 by Steven S Skiena

The Data Science Design Manual, 1st ed. 2017 by Steven S.
Skiena

The Python Workbook, 2014 by Ben Stephenson

UML @ Classroom, 2015 by Martina Seidl, Marion Scholz, Christian
Huemer, Gerti Kappel

Understanding Cryptography, 2010 by Christof Paar, Jan Pelzl

Fundamentals of Business Process Management, 2nd ed. 2018 by Marlon
Dumas, Marcello La Rosa, Jan Mendling, Hajo A. Reijers

Guide to Scientific Computing in C++, 2nd ed. 2017 by Joe
Pitt-Francis, Jonathan Whiteley

Fundamentals of Java Programming, 1st ed. 2018 by Mitsunori
Ogihara

Logical Foundations of Cyber-Physical Systems, 1st ed. 2018 by
André Platzer

Neural Networks and Deep Learning, 1st ed. 2018 by Charu C.
Aggarwal

Systems Programming in Unix/Linux, 1st ed. 2018 by K.C. Wang

Introduction to Parallel Computing, 1st ed. 2018 by Roman Trobec,
Boštjan Slivnik, Patricio Bulić, Borut Robič

Analysis for Computer Scientists, 2nd ed. 2018 by Michael
Oberguggenberger, Alexander Ostermann

Introductory Computer Forensics, 1st ed. 2018 by Xiaodong Lin

https://www.springernature.com/gp/librarians/the-link/blog/blogposts-ebooks/free-access-to-a-range-of-essential-textbooks/17855960


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