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About Deep Learning
The document discusses three axes of advancement in machine learning: network architectures, learning algorithms, and temporal/spatial hierarchy. It notes recurrent neural networks (RNNs) have improved over time through new architectures like LSTMs and GRUs that address the difficulty of training RNNs. RNNs are now achieving success in natural language processing tasks thanks to increased computational power, large datasets, and these new architectures that better model long-term dependencies.
Detailed Information
| Author: | ['Bob Assan'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 48 |
| Language: | English |
| Format: | |
| Price: | FREE |
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