jla524/fromthetensor resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1084 stars · 45 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A 10-week course outline for learning deep learning from first principles by implementing papers, from tensors up to Stable Diffusion. It includes example notebooks and video links, inspired by George Hotz's 'From the Transistor' approach.

Use cases

• learn deep learning from scratch in 10 weeks
• implement classic ML papers like AlexNet and ResNet
• understand transformers and stable diffusion from first principles
• find a structured self-study path to become an ML engineer
• practice building CNNs, RNNs, and GANs in PyTorch

When to choose

• you want a paper-implementation-driven deep learning curriculum
• you prefer hands-on notebooks over abstract tutorials
• you want to go from tensor basics to diffusion models

When to avoid

• you need a production library or tool rather than a course
• you want a polished, formally maintained course with support
• you are a complete beginner with no Python experience

Facets

learning-resource · maturity active

deep-learning machine-learning deep-learning machine-learning tutorials python course-outline pytorch transformers stable-diffusion self-study

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