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:

Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Introduction to the Math of Neural Networks - Jeff Heaton
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Pattern recognition and machine learning - Christopher M.Bishop
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Deep Learning in Python - LazyProgrammer
The hundred-page Machine Learning Book - Andriy Burkov
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Deep Learning with Hadoop - Dipayan Dev
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Machine Learning with Python for everyone - Mark E.Fenner
Medical Image Segmentation Using Artificial Neural Networks
Fundamentals of Deep Learning - Nikhil Bubuma
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Neural Networks and Deep Learning - Charu C.Aggarwal
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty