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:

Machine Learning with Python for everyone - Mark E.Fenner
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Introduction to Deep Learning - Eugene Charniak
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Deep Learning with Hadoop - Dipayan Dev
Python Machine Learning - Sebastian Raschka
Introduction to Scientific Programming with Python - Joakim Sundnes
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Learn Keras for Deep Neural Networks - Jojo Moolayil
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Deep Learning with Theano - Christopher Bourez
Python Machine Learning Eqution Reference - Sebastian Raschka
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Coding Theory - Algorithms, Architectures and Application
Pattern recognition and machine learning - Christopher M.Bishop
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Medical Image Segmentation Using Artificial Neural Networks
Java Deep Learning Essentials - Yusuke Sugomori
Deep Learning with Applications Using Python - Navin Kumar Manaswi