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About An Introduction To Deep Learning: January 2011
This document summarizes an introduction to deep learning presented at the European Symposium on Artificial Neural Networks in 2011. It discusses how deep learning uses multiple layers of nonlinear processing to automatically extract statistically robust features from data, avoiding the curse of dimensionality that affects shallow models. The key aspects of deep learning covered include using restricted Boltzmann machines to perform unsupervised layer-wise pre-training of deep networks before fine-tuning the entire network through supervised learning. Other deep learning models like stacked auto-encoders, deep kernel machines, and deep convolutional networks are also briefly discussed.
Detailed Information
| Author: | ['gmsaravanan'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 14 |
| Language: | English |
| Format: | |
| Price: | FREE |
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