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:

Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Pattern recognition and machine learning - Christopher M.Bishop
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Learn Keras for Deep Neural Networks - Jojo Moolayil
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Machine Learning with spark and python - Michael Bowles
Medical Image Segmentation Using Artificial Neural Networks
Neural Networks and Deep Learning - Charu C.Aggarwal
Introduction to Scientific Programming with Python - Joakim Sundnes
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Data Science and Big Data Analytics - EMC Education Services
Python Deep Learning Cookbook - Indra den Bakker
Deep Learning with Python - Francois Cholletf
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
R Deep Learning Essentials - Dr. Joshua F.Wiley
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Amazon Machine Learning Developer Guild Version Latest
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Machine Learning with Python for everyone - Mark E.Fenner
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
An introduction to neural networks - Kevin Gurney & University of Sheffield
Introduction to the Math of Neural Networks - Jeff Heaton