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 from Scratch - Building with Python form First Principles - Seth Weidman
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Deep Learning and Neural Networks - Jeff Heaton
Python Data Structures and Algorithms - Benjamin Baka
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Neural Networks - A visual introduction for beginners - Michael Taylor
Artificial Intelligence by example - Denis Rothman
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Deep Learning with Python - Francois Chollet
Amazon Machine Learning Developer Guild Version Latest
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Fundamentals of Deep Learning - Nikhil Bubuma
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Data Science and Big Data Analytics - EMC Education Services
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Deep Learning for Natural Language Processing - Jason Brownlee
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Deep Learning with Hadoop - Dipayan Dev
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Neural Networks and Deep Learning - Charu C.Aggarwal
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron