# elicit/machine-learning-list

A curriculum for learning about foundation models, from scratch to the frontier

Repository: https://github.com/elicit/machine-learning-list
Canonical: https://ross.abutalabs.com/products/machine-learning-list
Homepage: https://elicit.com/careers
License Family: other
Topics: artificial-intelligence, language-model, machine-learning, transformers
Last push: 2025-11-27T04:15:43+00:00

## Health v2 (maintenance only)
Score: 49/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 54, release rhythm 35, longevity 62
- inputs: {"age_days": 875, "days_push": 279, "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 1464, forks 125 (observed 2026-08-28T04:04:48.177796+00:00)

## What it is
A curated, tiered reading list and curriculum for learning machine learning with a focus on language models and foundation models, from fundamentals to frontier topics like scaling, safety, and interpretability. It is maintained by Elicit primarily to onboard new ML and software engineers.

## Use cases
- learn machine learning from scratch
- curriculum for understanding transformers and language models
- reading list of foundational ML papers
- onboarding material for ML engineers
- study foundation models and AI safety
- self-study path into deep learning and LLMs

## When to choose
- you want a structured, tiered path through ML and LLM literature
- you are onboarding engineers into ML-focused roles
- you want curated papers and videos rather than building software

## When to avoid
- you need runnable code, libraries, or tools
- you want interactive exercises or graded coursework
- you need a non-ML software engineering curriculum

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, llm-training, prompt-engineering, rag
- domain: machine-learning, deep-learning, large-language-models, artificial-intelligence, tutorials
- platform: cross-platform
- tags: curriculum, reading-list, foundation-models, transformers, papers, education

## Member repositories
- elicit/machine-learning-list (main) score 49

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:48.177796+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 2026-08-30T04:35:09.857816+00:00, confidence not recorded.
  - readme: https://github.com/elicit/machine-learning-list (fetched 2026-08-28T04:04:48.177796+00:00, sha 546f977e77aa)
  - homepage: https://elicit.com/careers (fetched 2026-08-29T11:44:02.580498+00:00, sha 721a74b42df2)
  - site_page: https://elicit.com/pricing (fetched 2026-08-29T11:44:02.589762+00:00, sha 8415a15efecd)
- Data as of 2026-08-30T08:39:29.467469+00:00.