Deep Learning: Technical Introduction
Overview & Synopsis
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.
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Document Information
| Document Title | Deep Learning: Technical Introduction |
|---|---|
| Author / Organization | Thomas Epelbaum |
| Subject & Discipline | Deep Learning and Neural Networks, Machine Learning, Data Science, Artificial Intelligence, Data Analysis and Data Mining |
| Categories | Deep Learning and Neural Networks |
| License / Rights | Creative Commons License (CC) |
| Resource Verification | ✓ Verified Direct PDF Available |
| Original Host Website |
FreeComputerBooks.com
(freecomputerbooks.com)
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| File Format | application/pdf (Portable Document Format) |
| Reported File Size | -0 KB (-1 bytes) |
| Language | ENGLISH |
| Catalog ID | DOC-93346 |
| Original Source Link | Visit Source Page on freecomputerbooks.com » |