# neomatrix369/awesome-ai-ml-dl

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

Repository: https://github.com/neomatrix369/awesome-ai-ml-dl
Canonical: https://ross.abutalabs.com/products/awesome-ai-ml-dl
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: ai, ml, dl, artificial-intelligence, machine-learning, deep-learning, neural-networks, algorithms, machine-intelligence, intelligent-systems, data, nlp, natural-language-processing, data-generation, time-series, graal, graalvm, docker, mathematica, cloud-devops
Last push: 2026-03-09T15:54:35+00:00

## Health v2 (maintenance only)
Score: 55/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 71, release rhythm 8, longevity 100
- inputs: {"age_days": 2810, "days_push": 177, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1709, forks 378 (observed 2026-08-28T04:05:25.557835+00:00)

## What it is
A curated awesome-list of artificial intelligence, machine learning, and deep learning resources, combining study notes with links to tools, courses, guides, and reference materials. It is organized by domain (NLP, time-series, data, agents) and by language ecosystem (Python, Java/JVM, others).

## Use cases
- find learning resources for machine learning
- curated list of AI and deep learning tutorials
- study notes for neural networks and NLP
- discover ML tools and frameworks by language
- learn data science and time-series basics
- find courses and competitions for AI beginners

## When to choose
- you want a broad, curated starting point for learning AI/ML/DL
- you need study notes alongside resource links
- you work across Python and JVM ecosystems and want resources for both

## When to avoid
- you need production-ready code or a maintained library
- you want a single structured course rather than a link collection
- you need up-to-date cutting-edge research papers only

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools
- domain: artificial-intelligence, machine-learning, deep-learning, tutorials, awesome-lists
- platform: cross-platform
- tags: awesome-list, study-notes, curated-resources, jupyter-notebooks, ai-education, natural-language-processing

## Member repositories
- neomatrix369/awesome-ai-ml-dl (main) score 55

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:25.557835+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 2026-08-30T03:36:58.670780+00:00, confidence not recorded.
  - readme: https://github.com/neomatrix369/awesome-ai-ml-dl (fetched 2026-08-28T04:05:25.557835+00:00, sha a26149850dac)
- Data as of 2026-08-30T08:39:29.467469+00:00.