# lukas/ml-class

Machine learning lessons and teaching projects designed for engineers

Repository: https://github.com/lukas/ml-class
Canonical: https://ross.abutalabs.com/products/ml-class
Homepage: https://www.youtube.com/channel/UCBp3w4DCEC64FZr4k9ROxig
Language: Jupyter Notebook
License: GPL-2.0
License Family: copyleft
Topics: machine-learning-tutorials, deep-learning-tutorials
Last push: 2024-06-27T09:51:07+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4019, "days_push": 797, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2593, forks 1182 (observed 2026-08-28T04:07:02.987185+00:00)

## What it is
A collection of bite-sized machine learning and deep learning tutorial projects for engineers, each with starter code in Jupyter Notebooks and an accompanying ~10 minute video. Projects progress from beginner (simple image classifiers) to advanced (RNNs, text generation) with no ML background assumed.

## Use cases
- learn deep learning from scratch
- build my first image classifier
- understand convolutional neural networks with hands-on code
- learn RNNs for time series prediction
- practice text classification and sentiment analysis
- find beginner machine learning tutorials with videos

## When to choose
- you're an engineer with Python skills but no ML background
- you want short, self-contained projects with video walkthroughs
- you prefer learning by running runnable notebook code

## When to avoid
- you need production ML tooling or a framework
- you want comprehensive theory or a full curriculum
- you need tutorials on modern LLMs or transformer architectures

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, nlp, computer-vision
- domain: machine-learning, deep-learning, tutorials, education
- platform: python, cross-platform
- tags: jupyter-notebooks, tutorials, deep-learning, beginner-friendly, videos, binder

## Member repositories
- lukas/ml-class (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:02.987185+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:22:16.690059+00:00, confidence not recorded.
  - readme: https://github.com/lukas/ml-class (fetched 2026-08-28T04:07:02.987185+00:00, sha 713098925b01)
  - homepage: https://www.youtube.com/channel/UCBp3w4DCEC64FZr4k9ROxig (fetched 2026-08-29T10:04:29.018791+00:00, sha 44136fa355b3)
- Data as of 2026-08-30T08:39:29.467469+00:00.