An effective "from scratch" CV learning path includes: first implementing a simple CNN to run on MNIST or CIFAR-10; reproducing the ResNet residual block and comparing the convergence difference with and without skip connections; manually implementing multi-head self-attention and building a mini-ViT; and reading the PyTorch source code; this methodology is in the same vein as Raschka: first get the code running, then understand why it is written this way, and finally modify the design and observe the effect.