# Bookmarks on Ebooks

## Ebook

* [Top Hacker News Books of All Time](https://hackernewsbooks.com/top-books-on-hacker-news)
* [Introduction to Information Retrieval](https://nlp.stanford.edu/IR-book/)
* [Plagiarism Checker - Graduateway](https://graduateway.com/plagiarism-checker/)
* [Ebookee: Free Download eBooks Search Engine!](https://www.ebookee.com/)
* [hypertextbook](https://hypertextbook.com/)

## Free Ebook

### Free Book on Neural Network (Artificial Intelligence)

* [Neural Nets](https://www.inf.ed.ac.uk/teaching/courses/nlu/assets/reading/Gurney_et_al.pdf)[,](http://www.shef.ac.uk/psychology/gurney/notes/download.html) Kevin Gurney
* [An Introduction to Artificial Neural Networks](http://arxiv.org/PS_cache/astro-ph/pdf/0102/0102224v1.pdf), C.A.L. Bailer-Jones berg, R. Gupta, H.P. Singh
* [Neural Networks](http://www.willamette.edu/~gorr/classes/cs449/intro.html), Genevieve Orr

1. [Introduction to Neural Networks](http://www.neuralnetworksolutions.com/resources.php)
2. [Machine Learning, Neural and Statistical Classification](http://www.maths.leeds.ac.uk/~charles/statlog/whole.pdf), D. Michie, D.J. Spiegelhalter, C.C. Taylor
3. [Planning Algorithms](http://planning.cs.uiuc.edu/booka4.pdf), Steven M. LaValle
4. [Introduction to Machine Learning](http://robotics.stanford.edu/people/nilsson/MLBOOK.pdf), Nils J. Nilsson
5. [Reinforcement Learning: An Introduction](http://www.cs.ualberta.ca/~sutton/book/ebook/the-book.html), Richard S. Sutton and Andrew G. Barto
6. [An Introduction to Neural Networks](http://lia.univ-avignon.fr/chercheurs/torres/livres/book-neuro-intro.pdf) Ben Krose, Patrick van der Smagt
7. [Neural Networks - A Systematic Introduction](http://www.inf.fu-berlin.de/inst/ag-ki/rojas_home/documents/1996/NeuralNetworks/neuron.pdf), Raul Rojas
8. [Neural Networks](http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html), Christos Stergiou and Dimitrios Siganos
9. [Dynamics of Complex Systems](http://necsi.org/publications/dcs/), Yaneer Bar-Yam
10. [Convex Optimization](http://www.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf), Stephen Boyd and Lieven Vandenberghe
11. [Reinforcement Learning:An Introduction](http://www.cs.ualberta.ca/~sutton/book/ebook/the-book.html), Richard S. Sutton, Andrew G. Barto
12. [Computing and the Brain](https://www.google.co.uk/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=2\&cad=rja\&uact=8\&ved=0CCgQFjAB\&url=http%3A%2F%2Fwww.cs.stir.ac.uk%2Fcourses%2F31YF%2Ftutorials%2Fbpg%2Ftut_neurons.pdf\&ei=rOlEVcbUG8bbU-e9gPgB\&usg=AFQjCNFC82OhU3qtO0uuG_jodf4aPuM7NA\&sig2=HoVFbxOQ714ObBg4wQW-Qg\&bvm=bv.92291466,d.d24), Dr Bruce Graham
13. [A Genetic Algorithm Tutorial](http://samizdat.mines.edu/ga_tutorial/ga_tutorial.ps), Darrell Whitley
14. [Artificial Intelligence through Prolog](https://www.google.co.uk/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=2\&cad=rja\&uact=8\&ved=0CCgQFjAB\&url=http%3A%2F%2Fcs.millersville.edu%2F~chaudhary%2F340%2FAIThruProlog.pdf\&ei=6elEVauuGonkUrW4gbAI\&usg=AFQjCNHJZBwdj3UkovoDr2qo-9x6Y0Empg\&sig2=h0hZzHBitHTQaYqcenFQyw\&bvm=bv.92291466,d.d24), Neil C. Rowe
15. [Brief Introduction to Educational Implications of Artificial Intelligenc](http://www.uoregon.edu/~moursund/Books/AIBook/AI.pdf), David Moursund
16. [Gaussian Processes for Machine Learning](http://www.gaussianprocess.org/gpml/chapters), Carl Edward Rasmussen and Christopher K. I. Williams
17. [Global Optimization Algorithms - Theory and Application](http://www.it-weise.de/projects/book.pdf), Thomas Weise
18. [Introduction to Neural Networks with Java](http://www.heatonresearch.com/articles/1), Jeff Heaton
19. [Practical Artificial Intelligence Programming in Java](https://archive.org/download/PracticalArtificialIntelligenceProgrammingWithJava/JavaAI3rd.pdf), Mark Watson
20. [Prolog and Natural-Language Analysis](http://www.mtome.com/Publications/PNLA/prolog-digital.pdf), Fernando C. N. Pereira, Stuart M. Shieber

### [Free Books on Information Theory and Communication System](https://free-ebook-download-links.blogspot.com/2008/06/free-book-on-wireless-communication.html)

1. [F**undamentals of Wireless Communication**](http://www.eecs.berkeley.edu/~dtse/book.html), David Tse and Pramod Viswanath
2. [An Introduction to Wireless Technology](http://www.redbooks.ibm.com/redbooks/pdfs/sg244465.pdf), IBM
3. [**Information Theory, Inference and Learning Algorithms**](http://www.inference.phy.cam.ac.uk/mackay/itila/book.html), David J. C. MacKay
4. [**Entropy and Information Theory**](http://www-ee.stanford.edu/~gray/it.pdf)**\*\*\*\*,** R.M. Gray
5. [Complexity Issues in Coding Theory](http://eccc.hpi-web.de/eccc-reports/1997/TR97-046/Paper.pdf), Alexander Barg
6. [Network Coding Theory](http://iest2.ie.cuhk.edu.hk/~whyeung/publications/tutorial.pdf), Raymond W. Yeung, Shuo-Yen Robert Li, Ning Cai and Zhen Zhang
7. [Notes on Coding Theory](http://www.mth.msu.edu/~jhall/classes/codenotes/coding-notes.html), Jonathan I. Hall
8. [**Theory of Codes**](http://projecteuclid.org/euclid.bams/1183553979), Jean Berstel, Dominique Perrin, C. Reutenauer
9. [Codes and Automata](https://www.google.co.uk/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=3\&cad=rja\&uact=8\&ved=0CCoQFjAC\&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.107.9934%26rep%3Drep1%26type%3Dpdf\&ei=DHVKVYaiHoKqUca_gPAK\&usg=AFQjCNH-z-D_ONBYxWwRmO4JsiKFz8BAcw\&sig2=rwSAS_bWNXfL565npZl1sQ\&bvm=bv.92291466,d.d24), Jean Berstel, Dominique Perrin, C. Reutenauer
10. [A Short Course in Information Theory](http://www.inference.phy.cam.ac.uk/mackay/info-theory/course.html), David J.C. MacKay
11. [Information, Randomness and Incompleteness](https://www.cs.auckland.ac.nz/~chaitin/ps3.pdf), G J Chaitin, IBM Research
12. [A Discipline Independent Definition of Information](http://www.ils.unc.edu/~losee/book5.pdf), Robert M. Losee
13. [A Mathematical Theory of Communication](https://www.google.co.uk/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=1\&cad=rja\&uact=8\&ved=0CCEQFjAA\&url=http%3A%2F%2Fworrydream.com%2Frefs%2FShannon%2520-%2520A%2520Mathematical%2520Theory%2520of%2520Communication.pdf\&ei=N3ZKVaOQD4feUdS2gOAK\&usg=AFQjCNEwXiWu_AGIt6URN277UWk3JaFu6Q\&sig2=yNuoPXsg4HrVfJuzKh38eQ\&bvm=bv.92291466,d.d24), Claude E. Shannon
14. [The Limits of Mathematics: A Course on Information Theory and the Limits of Formal Reasoning](https://www.google.co.uk/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=3\&cad=rja\&uact=8\&ved=0CC0QFjAC\&url=http%3A%2F%2Farxiv.org%2Fabs%2Fchao-dyn%2F9706010\&ei=VnZKVdn1AoG5UJOugNAN\&usg=AFQjCNEcf_hEIbPOH9xnS_zlD5G1ISvHYw\&sig2=QFW4TaLjO50qrE3jOL5-Ew\&bvm=bv.92291466,d.d24) , G J Chaitin
15. [UWB Communication Systems—A Comprehensive Overview](https://www.google.co.uk/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=2\&cad=rja\&uact=8\&ved=0CC0QFjAB\&url=http%3A%2F%2Fdownloads.hindawi.com%2Fbooks%2F9789775945105.pdf\&ei=eXZKVeahM8u2UaPJgdAK\&usg=AFQjCNH0tfdccErXJcnT06WZiJC_WHmXgg\&sig2=F1-JeiA4nG184yyiWYk7qw\&bvm=bv.92291466,d.d24), Edited by: Maria-Gabriella Di Benedetto, Thomas Kaiser, Andreas F.Molisch, Ian Oppermann, Christian Politano, and Domenico Porcino
16. [Introduction to Data Communications](http://www.cadvision.com/blanchas/Intro2dcRev2/index.html), by Eugene Blanchard
17. [Understanding Optical Communications](http://www.redbooks.ibm.com/redbooks/pdfs/sg245230.pdf)
18. [Asterisk: The Future of Telephony](https://www.google.co.uk/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=4\&cad=rja\&uact=8\&ved=0CDYQFjAD\&url=http%3A%2F%2Fcdn.oreillystatic.com%2Fbooks%2F9780596510480.pdf\&ei=o3ZKVeWsKcbyUpf0gfgK\&usg=AFQjCNGebvSLx4QZkAGfWPLOoKVGSzormw\&sig2=5vx5NbH77H_FkYAsMUnIJQ\&bvm=bv.92291466,d.d24), Jim Van Meggelen/Jared Smith/Leif Madsen
19. [Primer on Information Theory](ftp://ftp.ncifcrf.gov/pub/delila/primer.ps), Thomas Schneider
20. [A Discipline Independent Definition of Information](http://www.ils.unc.edu/~losee/book5.pdf), Robert M. Losee
21. [High-Speed Communication Circuits and Systems](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-976-high-speed-communication-circuits-and-systems-spring-2003/lecture-notes/lec1.pdf), Prof. Michael Perrott
22. [Communication System Design](http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-973Spring-2006/LectureNotes/index.htm), Prof. Vladimir Stojanovic
23. [Essential Coding Theory](http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-895Fall-2004/LectureNotes/index.htm), Prof. Madhu Sudan
24. [Speech Communication](http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-541JSpring2004/LectureNotes/index.htm), Prof. Kenneth Steven
25. [Quantum Optical Communication](http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-453Fall-2004/LectureNotes/index.htm), Prof. Jeffrey H. Shapiro
26. [Principles of Wireless Communications](http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-452Spring-2006/DownloadthisCourse/index.htm), Prof. Lizhong Zheng
27. [**Principles of Digital Communications I**](http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-450Fall-2006/DownloadthisCourse/index.htm)**, Prof. Robert Gallager, Prof. Lizhong Zheng**
28. [Principles of Digital Communication II](http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-451Spring-2005/CourseHome/index.htm), Prof. David Forney
29. [Quantum Information Science](http://ocw.mit.edu/OcwWeb/Media-Arts-and-Sciences/MAS-865JSpring-2006/LectureNotes/index.htm), Prof. Issac Chuang, Prof. Peter Shor
30. [Transmission of Information](http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-441Transmission-of-InformationSpring2003/LectureNotes/index.htm), Prof. Muriel Medard, Prof. Lizhong Zheng
31. [Data Communication Networks](http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-263JData-Communication-NetworksFall2002/LectureNotes/index.htm), Prof. Eytan Modiano
32. [Stochastic Processes, Detection, and Estimation](http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-432Spring2004/DownloadthisCourse/index.htm), Prof. Alan Willsky, Prof. Gregory Wornell
33. [Primer on Information Theory](ftp://ftp.ncifcrf.gov/pub/delila/primer.ps) by Thomas Schneider
34. [Stochastic Processes, Detection and Estimation](https://www.rle.mit.edu/sia/courses/stochastic-processes-detection-and-estimation/)-A. S. Willsky and G. W. Wornell

## eBook

* [Learn Python the Hard Way](https://learnpythonthehardway.org/book/)
* [22 Free Data Science Books](http://www.wzchen.com/data-science-books/)
* [Welcome · Advanced R.](http://adv-r.had.co.nz/)
* [PH525x series - Biomedical Data Science](https://genomicsclass.github.io/book/)
* [Neural networks and deep learning](http://neuralnetworksanddeeplearning.com/)
* [Mining of Massive Datasets](http://www.mmds.org/)
* [NLTK Book](http://www.nltk.org/book_1ed/)
* [**Data Journalism Handbook 2**](https://datajournalismhandbook.org/)–Online beta access to the first 21 chapters
* [**Select Star SQL**](https://selectstarsql.com/)–A book that is also a walk-through interactive tutorial for learning SQL
* [**Dive Into Deep Learning**](http://d2l.ai/)–A very detailed and up-to-date book on Deep Learning; used at Berkeley. It also includes Jupyter notebooks.
* [**R for Data Science**](https://r4ds.had.co.nz/)–Just like the title says, learn to use R for data science.
* [**Advanced R**](https://adv-r.hadley.nz/)–A work in progress for the second edition of the book.
* Foundations of Data Science–Free Book by Avrim Blum, John Hopcroft, and Ravindran Kannan wrote the book, [**Foundations of Data Science (PDF download)**](https://www.cs.cornell.edu/jeh/book.pdf).
* [**Introduction to Probability**](https://drive.google.com/file/d/1VmkAAGOYCTORq1wxSQqy255qLJjTNvBI/view) by Joseph Blitzstein and Jessica Hwang is available as a free PDF on Google Docs.
* Elements of Data Science–A free Jupyter Notebook Textbook [**Elements of Data Science**](https://allendowney.github.io/ElementsOfDataScience/) by Allen Downey is a freely available textbook.
* Free Reinforcement Learning Textbook. [**Reinforcement L**](http://incompleteideas.net/book/bookdraft2017nov5.pdf)[**earning: An Introduction**](http://incompleteideas.net/book/the-book-2nd.html) by Rich Sutton and Andrew Barto. The full text is available on a Google Drive at [Reinforcement Learning](https://drive.google.com/open?id=1opPSz5AZ_kVa1uWOdOiveNiBFiEOHjkG).
* Pablo Casas has published a book freely available online, [**Data Science Live Book**](https://livebook.datascienceheroes.com/).
* * [**Model-Based Machine Learning**](http://mbmlbook.com/)–Chapters of this book become available as they are being written. It introduces machine learning via case studies instead of just focusing on the algorithms.
* [**Foundations of Data Science**](https://www.cs.cornell.edu/jeh/book2016June9.pdf)–This is a much more academic-focused book which could be used at the undergraduate or graduate level. It covers many of the topics one would expect: machine learning, streaming, clustering and more.
* [**Deep Learning Book**](https://github.com/HFTrader/deepLearningBook)–This book was previously available only in [HTML form and not complete](http://ryanswanstrom.com/2015/04/29/free-deep-learning-book/). Now, it is free and downloadable.
* Professor Norm Matloff from the University of California, Davis has published [**From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science**](http://heather.cs.ucdavis.edu/matloff/public_html/probstatbook.html) which is an open textbook.
* [**Understanding Machine Learning: From Theory to Algorithms**](http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/) by [Shai Shalev-Shwartz](http://www.cs.huji.ac.il/~shais/), Associate Professor at the School of Computer Science and Engineering at The Hebrew University, Israel.
* [Hal Daumé III](http://hal3.name/), Assistant Professor of Computer Science at the University of Maryland, has placed the contents of his book online. The book is titled [**A Course in Machine Learning**](http://ciml.info/).