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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