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 Become a supporter of this podcast: https://www.spreaker.com/podcast/random-tech-thoughts--2829929/support.
