GET STARTED WITH A COLLECTION OF 247 FREE COMPUTER SCIENCE BOOKS

GET STARTED WITH A COLLECTION OF 247 FREE COMPUTER SCIENCE BOOKS

1. 10 Print – Free ebook from MIT Press about Commodore 64 BASIC
2. A Byte of Python
3. A Computer Science Tapestry: Exploring Programming and Computer Science with C++ by Astrachan
4. A Course in Machine Learning
5. A Field Guide to Genetic Programming
6. A First Course on Time Series Analysis with Examples in SAS
7. A Machine Made This Book: Ten Sketches Of Computer Science
8. A New Kind of Science by Stephen Wolfram
9. A Pamphlet against R: Computational Intelligence in Guile Scheme
10. A Practical Introduction to Data Structures and Algorithm Analysis by Clifford A. Shaffer
11. A Quick and Gentle Guide to Constraint Logic Programming via ECLiPSe by Antoni Niederlinski
12. Advanced Data Analysis from an Elementary Point of View by Cosma Rohilla Shalizi
13. Advances In Genetic Programming 3 by Lee Spector, William B. Langdon, Una-May O’Reilly and Peter J. Angeline
14. Algorithmic Mathematics
15. Algorithms and Data Structures for External Memory (Series on Foundations and Trends in Theoretical Computer Science) by Jeffrey S. Vitter
16. Algorithms for Clustering Data by Jain and Dubes
17. Algorithms Illuminated (video book)
18. Algorithms 4th Edition by Robert Sedgewick and Kevin Wayne
19. Algorithms by Jeff Erickson
20. An implementation of J
21. An Introduction to Functional Programming Through Lambda Calculus/Elementary Standard ML by Greg Michaelson
22. An Introduction to Probabilistic Programming
23. Anisotropic Diffusion in Image Processing by Joachim Weickert
24. Applied Mathematical Programming
25. Artificial Intelligence: Foundations of Computational Agents by David Poole, Alan Mackworth
26. ASN.1 Communication between Heterogeneous Systems by Olivier Dubuisson
27. Assemblers And Loaders
28. Basic Data Analysis and More: A Guided Tour Using Python
29. Basics of Compiler Design
30. Beej’s Guide to Network Programming
31. Blast from the Past: Unix text Processing
32. Building Blocks for Theoretical Computer Science by Margaret M. Fleck
33. C# Yellow Book by Rob Miles
34. Calculus by Gilbert Strang
35. Capability Based Computer Systems
36. Category Theory for Computing Science by Michael Barr and Charles Wells
37. Category Theory for Programmers by Bartosz Milewski
38. Certified Programming with Dependent Types
39. Clean Architectures in Python
40. Clever Algorithms: Nature-Inspired Programming Recipes
41. CODD: The relational model for database management
42. Combinatorial Algorithms 2nd Edition by Herbert Wilf
43. Combinatorial Optimization: Exact and Approximate Algorithms
44. Common Lisp: A Gentle Introduction to Symbolic Computation
45. Communicating Sequential Processes (CSP) by C.A.R. Hoare
46. Communication Network Analysis
47. Compiler Construction by Niklaus Wirth
48. Think Complexity by Allen B. Downey
49. Computational Statistics with Python (2017 edition)
50. Computer Organization and Design Fundamentals
51. Computer Science I
52. Computer Science: Abstraction to Implementation by Keller
53. Computer Vision: Algorithms and Applications
54. Computers and Thought: A practical Introduction to Artificial Intelligence
55. Computers in Communication by Gordon Brebner
56. Concrete Abstractions: An Introduction to Computer Science Using Scheme by Hailperin, Kaiser and Knight
57. Concrete Semantics
58. Convex Optimization by Stephen Boyd and Lieven Vandenberghe
59. Crafting Interpreters
60. Cryptography and Data Security by Denning
61. Cryptography: An Introduction by Nigel Smart
62. Data Structures & Algorithm Analysis (Edition 3.2) by Clifford A. Shaffer
63. Data Structures and Algorithms: The Basic Toolbox by Kurt Mehlhorn,Peter Sanders
64. Deep Learning by Goodfellow, Bengio, & Courville
65. Denotational Semantics: A Methodology for Language Development by Schmidt
66. Design of Approximation Algorithms by David P. Williamson and David B. Shmoys
67. Designing and Building Parallel Programs
68. Digraphs: Theory, Algorithms and Applications 1st Edition
69. Distributed Control of Robotic Networks by Bullo, Cortez, Martinez
70. Distributed systems for Fun and Profit
71. Distributed Systems 3rd Edition by Van Steen & Tannenbaum
72. Eloquent JavaScript
73. Entropy and Information Theory by Robert M. Gray
74. Essentials of Metaheuristics
75. Evolved to Win by Moshe Sipper
76. F# Succinctly (requires registration)
77. Finding Source Code on the Web for Remix and Reuse
78. Forecasting: Principles And Practice
79. Foundations of Computer Science by Aho and Ullman
80. Foundations of Databases: A book on design of databases
81. Foundations of Statistical Natural Language Processing
82. Free CS articles used at KTH in Stockholm: Basic algorithms, data structures and algorithm analysis, plenty of code examples.
83. 26 Free Smalltalk ebooks
84. From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science (HTML)
85. Functional Programming in OCaml by Michael Clarkson
86. Game Programming Patterns by Robert Nystrom
87. Gaussian Processes for Machine Learning by Carl E. Rasmussen, Christopher K. I. Williams
88. GPU Gems 2: Programming Techniques for High-Performance Graphics
89. GPU Gems 3: 3D and General Programming Techniques for GPUs
90. GPU Gems: 3D Programming Techniques, Tips, and Tricks
91. GPU Gems: Programming Techniques, Tips and Tricks for Real-Time Graphics
92. Handbook of Applied Cryptography
93. Haskell Book
94. Higher-Order Perl by Mark Jason Dominus
95. Hoare: Essays in computing science
96. How to Design Programs
97. How to Think Like a Computer Scientist in Python, Java, and C++
98. How to Use Scheme
99. Human JavaScript by Henry Joreteg
100. Implementing Functional Languages
101. Implementing Programming Languages
102. Information Theory, Inference, and Learning Algorithms
103. Introduction to Computing: Explorations in Language, Logic, and Machines by David Evans
104. Introduction to Deep Computer Vision
105. Introduction to Information Retrieval
106. Introduction to Machine Learning
107. Introduction to statistical thought by Michael L. Lavine
108. Introduction to Theory of Computation
109. Invent with Python
110. Is Parallel Programming Hard, And What Can You Do About It.
111. Learn C: Build Your Own Lisp
112. Learn Prolog Now! by Patrick Blackburn, Johan Bos, and Kristina Striegnitz
113. Learn Python the Hard Way 3rd Edition by Zed A. Shaw
114. Learning JavaScript Design Patterns
115. Let Over Lambda
116. Linux Device Drivers 3rd Edition
117. Linux Kernel in a Nutshell by Greg Kroah-Hartman
118. Logic for Computer Science: Foundations of Automatic Theorem Proving by Gallier
119. Logic, Programming and Prolog 2nd Edition by Ulf Nilsson and Jan Maluszynski
120. Machine Learning, Neural and Statistical Classification by Michie, Spiegelhalter and Taylor
121. Math and Computation by Avi Wigderson
122. Mathematics for Computer Science by Lehman & Leighton
123. Mathematics for Computer Science by Eric Lehman, F. Thomson Leighton, Albert R. Meyer (CCBYNCSA)
124. Matters Computational formerly Algorithms for Programmers by Jörg Arndt
125. Mercurial: The Definitive Guide
126. Prolog Programming in Depth and Natural Language Processing for Prolog Programmers by Michael A. Covington
127. Mining of Massive Datasets
128. MMURTL V1.0 aka Developing Your own 32 Bit Operating System
129. Modern Computer Arithmetic
130. Most Influential Books for Programmers
131. Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
132. Natural Image Statistics: A Probabilistic Approach to Early Computation Vision by Hyvärinen, Hurri and Hoyer
133. Natural Language Processing Techniques in Prolog by Patrick Blackburn and Kristina Striegnitz
134. Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit by Steven Bird, Ewan Klein, and Edward Loper
135. Nature of Code
136. Networks, Crowds, and Markets: Reasoning about a Highly Connected World by Easley, Kleinberg
137. Neural Network Design
138. Neural Networks – A Systematic Introduction
139. Neural Networks and Deep Learning
140. Node.js Succinctly by Emanuele DelBono
141. Non-Uniform Random Variate Generation
142. Notes on Theory of Distributed Systems (Yale CPSC 465/565: Fall 2017 Course Notes)
143. Open Government by Aaron Swartz
144. O’Reilly’s Real World OCaml
145. Object-oriented Programming in Javaâ„¢
146. Object-Oriented Programming with ANSI-C
147. Object-Oriented Reengineering Patterns
148. On Lisp: A Comprehensive Study of Advanced Lisp Techniques
149. Open Data Structures by Pat 
150. Operating Systems and Middleware: Supporting Controlled Interaction by Max Hailperin
151. Operating Systems: Three Easy Pieces
152. Optimized Numerical Algorithms Book and Implementations
153. Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp by Peter Norvig
154. Parallel and Distributed Computation: Numerical Methods by Dimitri P. Bertsekas and John Tsitsiklis. Athena Scientific
155. Partial Evaluation and Automatic Program Generation by Jones, Gomard, Sestoft
156. PC Assembly
157. Perl 6 at a Glance by Andrew Shitov
158. Peter Shirley’s Ray Tracing Books
159. Physically Based Rendering: From Theory to Implementation
160. Planning Algorithms / Motion Planning by Steven M. LaValle
161. Porting UNIX Software
162. Practical Common Lisp
163. Practical File System Design with the Be File System by Dominic Giampaolo
164. Concepts and Applications of Inferential Statistics by Richard Lowry
165. Principles of Computer System Design: An Introduction
166. Principles of Distributed Computing by Roger Wattenhofer
167. Probabilistic Models of Cognition
168. Problem Solving with Algorithms and Data Structures using Python
169. Producing Open Source Software
170. Professor Frisby’s Mostly Adequate Guide to Functional Programming
171. Programming and Programming Languages
172. Programming Books for Professionals
173. Programming from the Ground Up
174. Programming in D by Ali Çehreli
175. Programming in Lua 1st Edition
176. Programming Languages: Application and Interpretation by Shriram Krishnamurthi
177. Programming on Parallel Machines – GPU, Multicore, Clusters and More
178. Proofs and Types
179. Purely Functional Data Structures
180. Python 3 Patterns, Recipes and Idioms
181. Python Data Science Handbook
182. Quantitative System Performance: Computer System Analysis Using Queueing Network Models
183. Readings in Database Systems 5th Edition
184. Reinforcement Learning And Optimal Control
185. Scratchapixel: Learn Computer Graphics From Scratch!
186. Do It Yourself Agile 2nd Edition
187. Security Engineering by Anderson
188. Semantic Mining of Social Networks
189. ShaderX Books : ShaderX, ShaderX2: Intro & Tutorials, Tips & Tricks by Engel
190. SICP 2nd Edition
191. Simply Scheme: Introducing Computer Science 2nd Edition by Brian Harvey, Matthew Wright
192. Software Design Using C++ by Br. David Carlson
193. Software Engineering for Internet Applications by Andersson, Greenspun, Grumet
194. 4 Volumes of Software Foundations
195. Specification Case Studies 2nd Ed by Ian Hayes
196. Speech and Language Processing by Jurafsky, Martin
197. Stack Computers: The New Wave by Philip J. Koopman, Jr.
198. Stanford CS Book: Mining of Massive Datasets by Rajaraman, Ullman
199. Starting Forth by Leo Brodie
200. Strange Attractors: Creating Patterns in Chaos by Sprott
201. Successful Lisp
202. Reinforcement Learning: An Introduction by Sutton & Barto
203. Syncfusion Series of E-books (Assembly, C++, ASP.NET, Data Structures, etc)
204. Teach Yourself Scheme in Fixnum Days by Dorai Sitaram
205. Text Algorithms by M. Crochemore / W. Rytter
206. The Algorithmic Beauty of Plants by Przemyslaw Prusinkiewicz and Aristid Lindenmayer
207. The Ancient Art of the Numerati: A Programmer’s Guide to Data Mining)
208. The Architecture of Open Source Applications
209. The Art of Unix Programming
210. The C Book
211. The Computer Revolution In Philosophy: Philosophy, Science and Models of Mind
212. The Craft of Programming by Reynolds
213. The Craft of Text Editing
214. The Debian Administrator’s Handbook
215. The Design and Implementation of Probabilistic Programming Languages by N. D. Goodman and A. Stuhlmüller
216. The Design of Approximation Algorithms
217. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
218. The Haskell Road to Logic, Math and Programming by Doets and van Eijck
219. The HoTT Book | Homotopy Type Theory
220. The Hundred-Page Machine Learning Book by Andriy Burkov
221. The Implementation of Functional Programming Languages, by Simon Peyton Jones
222. The Internals of PostgreSQL
223. The Linux Command Line by William Shotts
224. The Little 
225. operating system
225. The Matrix Calculus You Need for Deep Learning by Terence Parr and Jeremy Howard
226. The OpenGL Programming Guide by The Redbook
227. The Playful Machine: Theoretical Foundation and Practical Realization of Self-Organizing Robots
228. The Power of Prolog
229. The Quest for Artificial Intelligence – A History of Ideas and Achievements – by Nils J. Nilsson (Stanford University)
230. The Scheme Programming Language, 4th Edition
231. The Scientist and Engineer’s Guide to Digital Signal Processing by Dr. Steven W. Smith
232. The Theory and Practice of Concurrency by A. W. Roscoe
233. The Ultimate Question of Programming, Refactoring, and Everything
234. The Way To Go: A Thorough Introduction to the Go Programming Language
235. Think Bayes: Bayesian Statistics Made Simple – Allen B. Downey
236. Think DSP – Digital Signal Processing in Python
237. Think Stats: Probability and Statistics for Programmers
238. Thinking Forth
239. Type Theory and Functional Programming
240. Understanding and Writing Compilers – Richard Bornat
241. UNIX Text Processing
242. Using Z: Specification, Refinement, and Proof (Formal techniques and formal methods for software engineering)
243. Vector Models for Data-Parallel Computing – Guy Blelloch
244. VT330/VT340 Programmer Reference Manual – Volume 2: Graphics Programming
245. Web Data Management (Abiteboul, Manolescu, Rigaux, Rousset, & Senellart. Cambridge University Press, 2011)
246. What the C or C++ Programmer Needs to Know About C# and the .NET Framework – Charles Petzold
247. xv6 – a simple, Unix-like teaching operating system

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