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:

Introduction to Deep Learning - Eugene Charniak
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Introduction to the Math of Neural Networks - Jeff Heaton
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Introduction to Scientific Programming with Python - Joakim Sundnes
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Python Machine Learning Eqution Reference - Sebastian Raschka
Learn Keras for Deep Neural Networks - Jojo Moolayil
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Artificial Intelligence by example - Denis Rothman
Deep Learning with PyTorch - Vishnu Subramanian
Data Science and Big Data Analytics - EMC Education Services
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Amazon Machine Learning Developer Guild Version Latest
Deep Learning for Natural Language Processing - Jason Brownlee
Neural Networks - A visual introduction for beginners - Michael Taylor
Fundamentals of Deep Learning - Nikhil Bubuma
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Medical Image Segmentation Using Artificial Neural Networks