# ByteByteGoHq/ml-bytebytego

Repository: https://github.com/ByteByteGoHq/ml-bytebytego
Canonical: https://ross.abutalabs.com/products/ml-bytebytego
License Family: other
Last push: 2025-05-13T17:46:41+00:00

## Health v2 (maintenance only)
Score: 41/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 21, release rhythm 35, longevity 96
- inputs: {"age_days": 1357, "days_push": 477, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1101, forks 223 (observed 2026-08-28T04:03:35.635230+00:00)

## What it is
A curated collection of reference materials and links for machine learning system design interview preparation, associated with ByteByteGo. It organizes external articles, papers, and documentation by chapter topics like data, modeling, and optimization.

## Use cases
- prepare for an ML system design interview
- find reading materials on machine learning fundamentals
- study topics like loss functions and optimization algorithms
- review ensemble learning and regularization concepts
- get a structured ML interview study guide

## When to choose
- you are preparing for machine learning system design interviews
- you want a curated index of ML learning resources
- you prefer organized external references over a full textbook

## When to avoid
- you need runnable code or a software library
- you want a complete self-contained course rather than links
- you need production ML tooling

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, documentation
- domain: machine-learning, tutorials, education
- platform: cross-platform
- tags: ml-system-design, interview-preparation, reference-materials, awesome-list

## Member repositories
- ByteByteGoHq/ml-bytebytego (main) score 41

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:35.635230+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 2026-08-30T06:45:40.707694+00:00, confidence not recorded.
  - readme: https://github.com/ByteByteGoHq/ml-bytebytego (fetched 2026-08-28T04:03:35.635230+00:00, sha b61d4ae928fe)
- Data as of 2026-08-30T08:39:29.467469+00:00.