Deep Learning · MT2 · section
The one page method map
Formula reference and exam revision
| Question clue | First action | Core formula or check |
|---|---|---|
| Neuron output | Multiply each input by its matching weight | z=\sum_iw_ix_i+b, then activate |
| Network prediction | Finish one whole layer before the next | h=f(Wx+b) |
| Backpropagation | State loss then prediction-minus-target | delta times sending activation |
| Optimizer update | Identify current gradient and stored state | old parameter minus update |
| CNN dimensions | Write N K S P and channels | \left\lfloor\frac{N+2P-K}{S}\right\rfloor+1 |
| CNN parameters | Count one filter then all filters | (K^2C_{\mathrm{in}}+1)C_{\mathrm{out}} |
| Pooling | Draw every valid window | Maximum, or mean of the window |
| Dense parameters | Count connections and receiving biases | (N_{\mathrm{in}}+1)N_{\mathrm{out}} |