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:

Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Python Data Structures and Algorithms - Benjamin Baka
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Introduction to Deep Learning - Eugene Charniak
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Deep Learning for Natural Language Processing - Jason Brownlee
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Medical Image Segmentation Using Artificial Neural Networks
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Machine Learning with spark and python - Michael Bowles
An introduction to neural networks - Kevin Gurney & University of Sheffield
Deep Learning with PyTorch - Vishnu Subramanian
Deep Learning with Theano - Christopher Bourez
Python Machine Learning - Sebastian Raschka
Introduction to the Math of Neural Networks - Jeff Heaton
Machine Learning with Python for everyone - Mark E.Fenner
Fundamentals of Deep Learning - Nikhil Bubuma
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Pattern recognition and machine learning - Christopher M.Bishop
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Deep Learning in Python - LazyProgrammer
Introduction to Scientific Programming with Python - Joakim Sundnes
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
R Deep Learning Essentials - Dr. Joshua F.Wiley