kuleshov/cornell-cs5785-2020-applied-ml resource
Teaching materials for the applied machine learning course at Cornell Tech (online edition) observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1986
- days_rel: n/a
- days_push: 1421
- n_releases_24m: 0
Adoption not part of the score
1181 stars · 288 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Executable Jupyter notebook course notes and slides for Cornell Tech's Applied Machine Learning (CS5785) Fall 2020 course, accompanied by YouTube lecture videos. It is a free educational resource covering practical machine learning concepts.
Use cases
- learn applied machine learning from a university course
- find lecture notes and slides for ML coursework
- run executable ML notebooks to study concepts
- self-study machine learning with video lectures
- use course materials for teaching an ML class
- review supervised and unsupervised learning examples
When to choose
- you want structured, university-quality ML course materials for free
- you prefer learning via runnable Jupyter notebooks paired with video lectures
- you need teaching materials for an applied ML course
When to avoid
- you need a production ML library or tool rather than educational content
- you require actively updated materials reflecting the latest ML research
- you need licensed or supported software for commercial use
Facets
learning-resource · maturity maintenance
machine-learning data-science machine-learning education tutorials python cross-platform course-materials jupyter-notebooks cornell-tech lecture-notes applied-ml
1 source
- readme: https://github.com/kuleshov/cornell-cs5785-2020-applied-ml · fetched 2026-08-28 · 4776e257885c
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| kuleshov/cornell-cs5785-2020-applied-ml | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="kuleshov/cornell-cs5785-2020-applied-ml")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem