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About The Functions of Deep Learning: Gilbert Strang
Deep learning uses continuous piecewise linear (CPL) functions to model complex relationships in data. CPL functions are composed of multiple linear pieces joined continuously. They can approximate complex functions while remaining feasible to compute. Neural networks implement CPL functions using layers of linear and ReLU activation functions. Weights connecting the layers are optimized using gradient descent to minimize error on training examples, enabling the network to generalize to new data. This approach has achieved breakthrough results in tasks like image recognition compared to previous shallow learning methods.
Detailed Information
| Author: | ['Gurpinder Singh'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 1 |
| Language: | English |
| Format: | |
| Price: | FREE |
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