Neural Networks and Deep Learning
by Michael Nielsen
Number of pages: 235
Neural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.
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by LISA lab - University of Montreal
This book will introduce you to some of the most important deep learning algorithms and show you how to run them using Theano. Theano is a python library that makes writing deep learning models easy, and gives the option of training them on a GPU.
by Juergen Schmidhuber - arXiv
In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarises relevant work, much of it from the previous millennium.
by Yoshua Bengio, Ian Goodfellow, Aaron Courville - MIT Press
This book can be useful for the university students learning about machine learning and the practitioners of machine learning, artificial intelligence, data-mining and data science aiming to better understand and take advantage of deep learning.
by Thomas Epelbaum - arXiv.org
This note presents in a technical though hopefully pedagogical way the three most common forms of neural network architectures: Feedforward, Convolutional and Recurrent. For each network, their fundamental building blocks are detailed.