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 Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Java Deep Learning Essentials - Yusuke Sugomori
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Neural Networks - A visual introduction for beginners - Michael Taylor
Python Machine Learning Eqution Reference - Sebastian Raschka
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning with Python - Francois Cholletf
Deep Learning with PyTorch - Vishnu Subramanian
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Learn Keras for Deep Neural Networks - Jojo Moolayil
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Pattern recognition and machine learning - Christopher M.Bishop
Deep Learning with Theano - Christopher Bourez
Fundamentals of Deep Learning - Nikhil Bubuma
Introduction to Deep Learning - Eugene Charniak
Introduction to the Math of Neural Networks - Jeff Heaton
Medical Image Segmentation Using Artificial Neural Networks
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Intelligent Projects Using Python - Santanu Pattanayak
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...