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 Title: Deep Learning: Technical Introduction
 Author(s) Thomas Epelbaum
 Publisher: Arxiv (2017)
 Hardcover/Paperback: N/A
 eBook: PDF
 Language: English
 ISBN10: N/A
 ISBN13: N/A
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Book Description
This book 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. The forward pass and the update rules for the backpropagation algorithm are then derived in full.
It could be the first stop for deep learning beginners, as it contains lots of concrete, easytofollow examples with corresponding tutorial videos and code notebooks.
 The science behind deep learning
 Building and training your own neural networks
 Privacy concepts, including federated learning
 Tips for continuing your pursuit of deep learning
 N/A
 Deep Learning and Neural Networks
 Machine Learning
 Data Science
 Artificial Intelligence
 Data Analysis and Data Mining

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