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 Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Machine Learning with Python for everyone - Mark E.Fenner
Coding Theory - Algorithms, Architectures and Application
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Python Deep Learning Cookbook - Indra den Bakker
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Artificial Intelligence by example - Denis Rothman
Fundamentals of Deep Learning - Nikhil Bubuma
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Java Deep Learning Essentials - Yusuke Sugomori
Introduction to the Math of Neural Networks - Jeff Heaton
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
The hundred-page Machine Learning Book - Andriy Burkov
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Python Machine Learning Eqution Reference - Sebastian Raschka
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Deep Learning with Python - Francois Chollet
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Introduction to Deep Learning - Eugene Charniak
Medical Image Segmentation Using Artificial Neural Networks
Neural Networks and Deep Learning - Charu C.Aggarwal
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain