Summary – CNN Pattern Detection Tutorial
- A CNN learns pattern detectors (kernels) automatically by minimizing a loss function.
- It starts with random filters, computes activations and outputs, and uses backpropagation to update filters.
- We just need: input, convolution, activation, output, and update steps.
Next – Kernel in Regression