Deep Learning – Ian Goodfellow & Yoshua Bengio & Aaron Courville

We would like to thank those who commented on our proposal for the book and helped plan its contents and organization: Guillaume Alain, Kyunghyun Cho, Çağlar Gülçehre, David Krueger, Hugo Larochelle, Razvan Pascanu and Thomas Rohée.

We would like to thank the people who offered feedback on the content of the book itself. Some offered feedback on many chapters: Martín Abadi, Guillaume Alain, Ion Androutsopoulos, Fred Bertsch, Olexa Bilaniuk, Ufuk Can Biçici, Matko Bošnjak, John Boersma, Greg Brockman, Alexandre de Brébisson, Pierre Luc Carrier, Sarath Chandar, Pawel Chilinski, Mark Daoust, Oleg Dashevskii, Laurent Dinh, Stephan Dreseitl, Jim Fan, Miao Fan, Meire Fortunato, Frédéric Francis, Nando de Freitas, Çağlar Gülçehre, Jurgen Van Gael, Javier Alonso García, Jonathan Hunt, Gopi Jeyaram, Chingiz Kabytayev, Lukasz Kaiser, Varun Kanade, Asifullah Khan, Akiel Khan, John King, Diederik P. Kingma, Yann LeCun, Rudolf Mathey, Matías Mattamala, Abhinav Maurya, Kevin Murphy, Oleg Mürk, Roman Novak, Augustus Q. Odena, Simon Pavlik, Karl Pichotta, Eddie Pierce, Kari Pulli, Roussel Rahman, Tapani Raiko, Anurag Ranjan, Johannes Roith, Mihaela Rosca, Halis Sak, César Salgado, Grigory Sapunov, Yoshinori Sasaki, Mike Schuster, Julian Serban, Nir Shabat, Ken Shirriff, Andre Simpelo, Scott Stanley, David Sussillo, Ilya Sutskever, Carles Gelada Sáez, Graham Taylor, Valentin Tolmer, Massimiliano Tomassoli, An Tran, Shubhendu Trivedi, Alexey Umnov, Vincent Vanhoucke, Marco Visentini-Scarzanella, Martin Vita, David Warde-Farley, Dustin Webb, Kelvin Xu, Wei Xue, Ke Yang, Li Yao, Zygmunt Zając and Ozan Çağlayan.

Related posts:

Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
The hundred-page Machine Learning Book - Andriy Burkov
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Deep Learning with Hadoop - Dipayan Dev
Deep Learning for Natural Language Processing - Jason Brownlee
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Fundamentals of Deep Learning - Nikhil Bubuma
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Pattern recognition and machine learning - Christopher M.Bishop
Introduction to Deep Learning - Eugene Charniak
R Deep Learning Essentials - Dr. Joshua F.Wiley
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Coding Theory - Algorithms, Architectures and Application
Neural Networks - A visual introduction for beginners - Michael Taylor
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Deep Learning with Python - Francois Chollet
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Machine Learning with Python for everyone - Mark E.Fenner
Deep Learning with Theano - Christopher Bourez
Machine Learning with spark and python - Michael Bowles
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden