| Name | First Aired | Runtime | Image | |
|---|---|---|---|---|
| S03E01 | Neural Networks Overview | 15 | ||
| S03E02 | Neural Network Representation | 15 | ||
| S03E03 | Computing a Neural Network's Output | 15 | ||
| S03E04 | Vectorizing across multiple examples | 15 | ||
| S03E05 | Explanation for Vectorized Implementation | 15 | ||
| S03E06 | Activation functions | 15 | ||
| S03E07 | Why do you need non-linear activation functions? | 15 | ||
| S03E08 | Derivatives of activation functions | 15 | ||
| S03E09 | Gradient descent for Neural Networks | 15 | ||
| S03E10 | Backpropagation intuition - optional | 15 | ||
| S03E11 | Random Initialization | 15 | ||
| S03E12 | Ian Goodfellow interview | 15 |
No artwork of this type.
No artwork of this type.
No artwork of this type.