Download Deep Learning Basics Lecture 1: Feedforward: Princeton University COS 495 Instructor: Yingyu Liang PDF Free - Full Version
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About Deep Learning Basics Lecture 1: Feedforward: Princeton University COS 495 Instructor: Yingyu Liang
1) The document discusses the basics of feedforward deep neural networks, including their motivation as a way to learn representations of data and model complex patterns. 2) Feedforward networks consist of layers of hidden units that apply nonlinear transformations to their inputs through activation functions like ReLU. 3) The output of each hidden layer is fed as input to the next layer, allowing the network to learn increasingly complex representations, with the last layer producing the final output such as a classification or regression value.
Detailed Information
| Author: | ['borelcantelli'] |
|---|---|
| Publication Year: | 2016 |
| Pages: | 31 |
| Language: | English |
| Format: | |
| Price: | FREE |
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