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 Applications Using Python - Navin Kumar Manaswi
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Deep Learning with Python - Francois Cholletf
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Artificial Intelligence by example - Denis Rothman
Java Deep Learning Essentials - Yusuke Sugomori
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
The hundred-page Machine Learning Book - Andriy Burkov
Amazon Machine Learning Developer Guild Version Latest
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Pattern recognition and machine learning - Christopher M.Bishop
Deep Learning and Neural Networks - Jeff Heaton
Deep Learning in Python - LazyProgrammer
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Learn Keras for Deep Neural Networks - Jojo Moolayil
Neural Networks - A visual introduction for beginners - Michael Taylor
Data Science and Big Data Analytics - EMC Education Services
Python Machine Learning - Sebastian Raschka
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Deep Learning with PyTorch - Vishnu Subramanian
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning for Natural Language Processing - Jason Brownlee
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman