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 - A Probabilistic Perspective - Kevin P.Murphy
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Pattern recognition and machine learning - Christopher M.Bishop
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Java Deep Learning Essentials - Yusuke Sugomori
Artificial Intelligence by example - Denis Rothman
Deep Learning with PyTorch - Vishnu Subramanian
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Neural Networks - A visual introduction for beginners - Michael Taylor
Python Machine Learning - Sebastian Raschka
Introduction to the Math of Neural Networks - Jeff Heaton
The hundred-page Machine Learning Book - Andriy Burkov
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Medical Image Segmentation Using Artificial Neural Networks
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Deep Learning with Python - Francois Chollet
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Neural Networks and Deep Learning - Charu C.Aggarwal
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain