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:

Neural Networks and Deep Learning - Charu C.Aggarwal
An introduction to neural networks - Kevin Gurney & University of Sheffield
Machine Learning with spark and python - Michael Bowles
Java Deep Learning Essentials - Yusuke Sugomori
Data Science and Big Data Analytics - EMC Education Services
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Machine Learning with Python for everyone - Mark E.Fenner
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Intelligent Projects Using Python - Santanu Pattanayak
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Medical Image Segmentation Using Artificial Neural Networks
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Deep Learning with Python - Francois Cholletf
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Introduction to Deep Learning - Eugene Charniak
The hundred-page Machine Learning Book - Andriy Burkov
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Python Data Structures and Algorithms - Benjamin Baka
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke