# b7leung/MLE-Flashcards

200+ detailed flashcards useful for reviewing topics in machine learning, computer vision, and computer science.

Repository: https://github.com/b7leung/MLE-Flashcards
Canonical: https://ross.abutalabs.com/products/mle-flashcards
License: GPL-3.0
License Family: copyleft
Topics: ai, artificial-intelligence, computer-vision, machine-learning, computer-science, flashcards, interview, interview-preparation, review
Last push: 2026-04-30T05:33:31+00:00

## Health v2 (maintenance only)
Score: 68/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 80, release rhythm 35, longevity 100
- inputs: {"age_days": 1502, "days_push": 125, "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 2506, forks 227 (observed 2026-08-28T04:06:57.142945+00:00)

## What it is
A collection of 250+ detailed flashcards covering machine learning, deep learning, computer vision, NLP, reinforcement learning, and generative models. It is a study and interview-preparation reference created from years of ML research and coursework, distributed as slide decks.

## Use cases
- prepare for machine learning engineer interviews
- review ML fundamentals before an exam
- brush up on computer vision concepts
- study deep learning and generative model topics
- find gaps in my ML knowledge before an interview
- get an overview of reinforcement learning and LLM topics

## When to choose
- you already have a solid ML foundation and want a concise review
- you are preparing for ML/CV job interviews
- you want a broad topic checklist spanning classical ML to NeRFs and LLMs

## When to avoid
- you are a complete beginner needing step-by-step tutorials
- you need a definitive, error-free textbook reference
- you want interactive spaced-repetition software rather than slide decks

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: machine-learning, computer-vision, artificial-intelligence, tutorials
- platform: cross-platform
- tags: flashcards, interview-preparation, study-notes, deep-learning, reinforcement-learning, nlp, generative-models

## Member repositories
- b7leung/MLE-Flashcards (main) score 68

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:57.142945+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 2026-08-30T02:26:42.215170+00:00, confidence not recorded.
  - readme: https://github.com/b7leung/MLE-Flashcards (fetched 2026-08-28T04:06:57.142945+00:00, sha 6d970d0a8db1)
- Data as of 2026-08-30T08:39:29.467469+00:00.