Choose the depth you want to explore
Neural Networks: Zero to Hero and Dive into Deep Learning offer paths into neural networks. Hands-On Machine Learning provides notebooks tied to the book, while Made With ML focuses on practical ML work. LLMs from Scratch and LLM Course narrow the focus to language models.
Plan for the working environment
Read the setup and prerequisites before choosing a path. A public repository can contain companion material for a book, and examples can need compute or external services. Use the source to identify what you can run locally, then work through one small example before scaling the exercise.
How this collection is selected
These catalog entries teach ML through code, notebooks, or extended explanations. They cover different depths and prerequisites; public repository access does not imply that companion books or compute are free.
Selection notes updated . Popularity metrics, when available, show their own snapshot date.