# afshinea/stanford-cs-230-deep-learning

VIP cheatsheets for Stanford's CS 230 Deep Learning

Repository: https://github.com/afshinea/stanford-cs-230-deep-learning
Canonical: https://ross.abutalabs.com/products/stanford-cs-230-deep-learning
Homepage: https://stanford.edu/~shervine/teaching/cs-230/
License: MIT
License Family: permissive
Topics: cheatsheet, deep-learning, convolutional-neural-networks, recurrent-neural-networks, data-science
Last push: 2020-05-20T04:23:57+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2836, "days_push": 2296, "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 7064, forks 1448 (observed 2026-08-28T04:09:55.649131+00:00)

## What it is
A collection of illustrated VIP cheatsheets (PDF and web) summarizing Stanford's CS 230 Deep Learning course, covering CNNs, RNNs, and deep learning tips and tricks. Available in multiple languages, it serves as a compact reference for students and practitioners.

## Use cases
- review deep learning concepts before an exam
- quick reference for CNN and RNN architectures
- study Stanford CS 230 course material
- brush up on training tips like regularization and initialization
- find a multilingual deep learning cheatsheet

## When to choose
- you want concise, illustrated summaries of core deep learning topics
- you are taking or teaching a deep learning course and need reference sheets
- you prefer quick-reference PDFs over long textbooks

## When to avoid
- you need hands-on code examples or tutorials
- you want up-to-date coverage of recent deep learning research
- you need a comprehensive textbook-level treatment

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, deep-learning, machine-learning
- domain: deep-learning, machine-learning, education, tutorials
- platform: cross-platform
- tags: cheatsheets, stanford-cs-230, cnn, rnn, study-notes, pdf

## Member repositories
- afshinea/stanford-cs-230-deep-learning (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:55.649131+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 2026-08-29T17:40:28.530312+00:00, confidence not recorded.
  - readme: https://github.com/afshinea/stanford-cs-230-deep-learning (fetched 2026-08-28T04:09:55.649131+00:00, sha 278fda317c21)
  - homepage: https://stanford.edu/~shervine/teaching/cs-230/ (fetched 2026-08-29T08:36:22.219969+00:00, sha 8f8b2ccbaf3a)
- Data as of 2026-08-30T08:39:29.467469+00:00.