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 with Keras - Antonio Gulli & Sujit Pal
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Python Machine Learning Eqution Reference - Sebastian Raschka
Medical Image Segmentation Using Artificial Neural Networks
Machine Learning with spark and python - Michael Bowles
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Deep Learning with PyTorch - Vishnu Subramanian
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Data Science and Big Data Analytics - EMC Education Services
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Introduction to Scientific Programming with Python - Joakim Sundnes
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Neural Networks and Deep Learning - Charu C.Aggarwal
Deep Learning and Neural Networks - Jeff Heaton
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Intelligent Projects Using Python - Santanu Pattanayak
Artificial Intelligence by example - Denis Rothman
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Introduction to Deep Learning - Eugene Charniak
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Python Data Structures and Algorithms - Benjamin Baka
Pattern recognition and machine learning - Christopher M.Bishop
Learn Keras for Deep Neural Networks - Jojo Moolayil
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho