Bookmarks on Ebooks
Ebook
- Top Hacker News Books of All Time
- Introduction to Information Retrieval
- Plagiarism Checker - Graduateway
- Ebookee: Free Download eBooks Search Engine!
- hypertextbook
Free Ebook
Free Book on Neural Network (Artificial Intelligence)
- Neural Nets, Kevin Gurney
- An Introduction to Artificial Neural Networks, C.A.L. Bailer-Jones berg, R. Gupta, H.P. Singh
- Neural Networks, Genevieve Orr
- Introduction to Neural Networks
- Machine Learning, Neural and Statistical Classification, D. Michie, D.J. Spiegelhalter, C.C. Taylor
- Planning Algorithms, Steven M. LaValle
- Introduction to Machine Learning, Nils J. Nilsson
- Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto
- An Introduction to Neural Networks Ben Krose, Patrick van der Smagt
- Neural Networks - A Systematic Introduction, Raul Rojas
- Neural Networks, Christos Stergiou and Dimitrios Siganos
- Dynamics of Complex Systems, Yaneer Bar-Yam
- Convex Optimization, Stephen Boyd and Lieven Vandenberghe
- Reinforcement Learning:An Introduction, Richard S. Sutton, Andrew G. Barto
- Computing and the Brain, Dr Bruce Graham
- A Genetic Algorithm Tutorial, Darrell Whitley
- Artificial Intelligence through Prolog, Neil C. Rowe
- Brief Introduction to Educational Implications of Artificial Intelligenc, David Moursund
- Gaussian Processes for Machine Learning, Carl Edward Rasmussen and Christopher K. I. Williams
- Global Optimization Algorithms - Theory and Application, Thomas Weise
- Introduction to Neural Networks with Java, Jeff Heaton
- Practical Artificial Intelligence Programming in Java, Mark Watson
- Prolog and Natural-Language Analysis, Fernando C. N. Pereira, Stuart M. Shieber
Free Books on Information Theory and Communication System
- Fundamentals of Wireless Communication, David Tse and Pramod Viswanath
- An Introduction to Wireless Technology, IBM
- Information Theory, Inference and Learning Algorithms, David J. C. MacKay
- Entropy and Information Theory**,** R.M. Gray
- Complexity Issues in Coding Theory, Alexander Barg
- Network Coding Theory, Raymond W. Yeung, Shuo-Yen Robert Li, Ning Cai and Zhen Zhang
- Notes on Coding Theory, Jonathan I. Hall
- Theory of Codes, Jean Berstel, Dominique Perrin, C. Reutenauer
- Codes and Automata, Jean Berstel, Dominique Perrin, C. Reutenauer
- A Short Course in Information Theory, David J.C. MacKay
- Information, Randomness and Incompleteness, G J Chaitin, IBM Research
- A Discipline Independent Definition of Information, Robert M. Losee
- A Mathematical Theory of Communication, Claude E. Shannon
- The Limits of Mathematics: A Course on Information Theory and the Limits of Formal Reasoning , G J Chaitin
- UWB Communication Systems—A Comprehensive Overview, Edited by: Maria-Gabriella Di Benedetto, Thomas Kaiser, Andreas F.Molisch, Ian Oppermann, Christian Politano, and Domenico Porcino
- Introduction to Data Communications, by Eugene Blanchard
- Understanding Optical Communications
- Asterisk: The Future of Telephony, Jim Van Meggelen/Jared Smith/Leif Madsen
- Primer on Information Theory, Thomas Schneider
- A Discipline Independent Definition of Information, Robert M. Losee
- High-Speed Communication Circuits and Systems, Prof. Michael Perrott
- Communication System Design, Prof. Vladimir Stojanovic
- Essential Coding Theory, Prof. Madhu Sudan
- Speech Communication, Prof. Kenneth Steven
- Quantum Optical Communication, Prof. Jeffrey H. Shapiro
- Principles of Wireless Communications, Prof. Lizhong Zheng
- Principles of Digital Communications I, Prof. Robert Gallager, Prof. Lizhong Zheng
- Principles of Digital Communication II, Prof. David Forney
- Quantum Information Science, Prof. Issac Chuang, Prof. Peter Shor
- Transmission of Information, Prof. Muriel Medard, Prof. Lizhong Zheng
- Data Communication Networks, Prof. Eytan Modiano
- Stochastic Processes, Detection, and Estimation, Prof. Alan Willsky, Prof. Gregory Wornell
- Primer on Information Theory by Thomas Schneider
- Stochastic Processes, Detection and Estimation-A. S. Willsky and G. W. Wornell
eBook
- Learn Python the Hard Way
- 22 Free Data Science Books
- Welcome · Advanced R.
- PH525x series - Biomedical Data Science
- Neural networks and deep learning
- Mining of Massive Datasets
- NLTK Book
- Data Journalism Handbook 2–Online beta access to the first 21 chapters
- Select Star SQL–A book that is also a walk-through interactive tutorial for learning SQL
- Dive Into Deep Learning–A very detailed and up-to-date book on Deep Learning; used at Berkeley. It also includes Jupyter notebooks.
- R for Data Science–Just like the title says, learn to use R for data science.
- Advanced R–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).
- Introduction to Probability 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 by Allen Downey is a freely available textbook.
- Free Reinforcement Learning Textbook. Reinforcement Learning: An Introduction by Rich Sutton and Andrew Barto. The full text is available on a Google Drive at Reinforcement Learning.
- Pablo Casas has published a book freely available online, Data Science Live Book.
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- Model-Based Machine Learning–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–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–This book was previously available only in HTML form and not complete. 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 which is an open textbook.
- Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz, Associate Professor at the School of Computer Science and Engineering at The Hebrew University, Israel.
- Hal Daumé III, 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.
