- Completing the blog series provides a solid understanding of deep learning basics, but there's much more to learn beyond this 20k-word introduction.
- Recommended resources include PyTorch documentation, Andrej Karpathy's micrograd and RNN posts, and FastAI's Jupyter notebooks.
- Notable projects for further learning: Whisper.cpp (speech recognition in C++) and Llama.cpp (large language model), both runnable on modest hardware.
- The author invites readers to contribute recommendations via pull requests or email.