Comparison
awesome-AutoML vs Awesome-AI-Data-Guided-Projects
Verdict
Pick awesome-AutoML if curates AutoML research across neural architecture search, hyperparameter optimization, and meta-learning; pick Awesome-AI-Data-Guided-Projects if awesome-AI-Data-Guided-Projects is a curated list featuring projects for building conversational chatbots using large language models and fine-tuning LLMs with LoRA, suitable for portfolio-building in AI.
Markdown twin · awesome-AutoML alternatives · Awesome-AI-Data-Guided-Projects alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | awesome-AutoML | Awesome-AI-Data-Guided-Projects |
|---|---|---|
| Maintenance | Slowing (133d since push) As of 2w · github_public_v1 | Dormant (817d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · github_public_v1 | Not a fork · Personal account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- awesome-AutoML
- Curating AutoML research and resources
- Awesome-AI-Data-Guided-Projects
- A curated list of data science & AI guided projects for portfolio-building
Stars
- awesome-AutoML
- 941
- Awesome-AI-Data-Guided-Projects
- 723
Forks
- awesome-AutoML
- 156
- Awesome-AI-Data-Guided-Projects
- 151
Open issues
- awesome-AutoML
- 1
- Awesome-AI-Data-Guided-Projects
- 2
Language
- awesome-AutoML
- -
- Awesome-AI-Data-Guided-Projects
- -
Adopt for
- awesome-AutoML
- Curates AutoML research across neural architecture search, hyperparameter optimization, and meta-learning.
- Awesome-AI-Data-Guided-Projects
- Awesome-AI-Data-Guided-Projects is a curated list featuring projects for building conversational chatbots using large language models and fine-tuning LLMs with LoRA, suitable for portfolio-building in AI.
Persona
- awesome-AutoML
- -
- Awesome-AI-Data-Guided-Projects
- -
Runtime
- awesome-AutoML
- -
- Awesome-AI-Data-Guided-Projects
- -
License
- awesome-AutoML
- GPL-3.0
- Awesome-AI-Data-Guided-Projects
- GPL-3.0 License allows free use for personal and commercial purposes but requires users to make their modifications available under the same license terms.
Last pushed
- awesome-AutoML
- Mar 24, 2026
- Awesome-AI-Data-Guided-Projects
- May 5, 2024
Categories
- awesome-AutoML
- Model Training
- Awesome-AI-Data-Guided-Projects
- Developer Tools, LLM Frameworks, Model Training
Trust and health
Maintenance
- awesome-AutoML
- Slowing (36%)
- Awesome-AI-Data-Guided-Projects
- Dormant (18%)
Days since push
- awesome-AutoML
- 133d
- Awesome-AI-Data-Guided-Projects
- 817d
Open issues (now)
- awesome-AutoML
- 1
- Awesome-AI-Data-Guided-Projects
- 2
Full report
- awesome-AutoML
- Trust report
- Awesome-AI-Data-Guided-Projects
- Trust report
Choose awesome-AutoML if…
- Tags unique to awesome-AutoML: automl, hyperparameter-optimization, meta-learning, neural-architecture-search.
- When seeking comprehensive resources on diverse AutoML topics from recent and impactful research.
- More GitHub stars (941 vs 723) - visibility, not fit.
When NOT to use awesome-AutoML
- If looking for direct implementation advice as the repository focuses more on linking to resources rather than providing specific how-to guides.
- When requiring real-time or interactive AutoML features, since it's a curation hub rather than an application tool.
Choose Awesome-AI-Data-Guided-Projects if…
- Tags unique to Awesome-AI-Data-Guided-Projects: ai, computer-vision, datascience, deep-learning.
- Also covers Developer Tools, LLM Frameworks.
- You need guided projects to build conversational chatbot applications.
When NOT to use Awesome-AI-Data-Guided-Projects
- Looking for end-to-end LLM training from scratch; this tool focuses more on fine-tuning and guided projects.
- In search of proprietary AI tools or custom enterprise solutions, as Awesome-AI-Data-Guided-Projects offers open-source project guides.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (windmaple/awesome-AutoML) · observed Aug 4, 2026
- GitHub forks (windmaple/awesome-AutoML) · observed Aug 4, 2026
- Last push (windmaple/awesome-AutoML) · observed Mar 24, 2026
- License file (GPL-3.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (youssefHosni/Awesome-AI-Data-Guided-Projects) · observed Jul 31, 2026
- GitHub forks (youssefHosni/Awesome-AI-Data-Guided-Projects) · observed Jul 31, 2026
- Last push (youssefHosni/Awesome-AI-Data-Guided-Projects) · observed May 5, 2024
- License file (GPL-3.0) · observed Jul 31, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-AutoML 941 · Awesome-AI-Data-Guided-Projects 723 (synced Aug 4, 2026).
Common questions
- What is the difference between awesome-AutoML and Awesome-AI-Data-Guided-Projects?
- awesome-AutoML: Curating AutoML research and resources. Awesome-AI-Data-Guided-Projects: A curated list of data science & AI guided projects for portfolio-building. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-AutoML over Awesome-AI-Data-Guided-Projects?
- Choose awesome-AutoML over Awesome-AI-Data-Guided-Projects when Tags unique to awesome-AutoML: automl, hyperparameter-optimization, meta-learning, neural-architecture-search; When seeking comprehensive resources on diverse AutoML topics from recent and impactful research; More GitHub stars (941 vs 723) - visibility, not fit.
- When should I choose Awesome-AI-Data-Guided-Projects over awesome-AutoML?
- Choose Awesome-AI-Data-Guided-Projects over awesome-AutoML when Tags unique to Awesome-AI-Data-Guided-Projects: ai, computer-vision, datascience, deep-learning; Also covers Developer Tools, LLM Frameworks; You need guided projects to build conversational chatbot applications.
- When should I avoid awesome-AutoML?
- If looking for direct implementation advice as the repository focuses more on linking to resources rather than providing specific how-to guides. When requiring real-time or interactive AutoML features, since it's a curation hub rather than an application tool.
- When should I avoid Awesome-AI-Data-Guided-Projects?
- Looking for end-to-end LLM training from scratch; this tool focuses more on fine-tuning and guided projects. In search of proprietary AI tools or custom enterprise solutions, as Awesome-AI-Data-Guided-Projects offers open-source project guides.
- Is awesome-AutoML or Awesome-AI-Data-Guided-Projects more popular on GitHub?
- awesome-AutoML has more GitHub stars (941 vs 723). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-AutoML and Awesome-AI-Data-Guided-Projects open source?
- Yes - both are open-source projects on GitHub (awesome-AutoML: GPL-3.0, Awesome-AI-Data-Guided-Projects: GPL-3.0).
- Where can I find alternatives to awesome-AutoML or Awesome-AI-Data-Guided-Projects?
- GraphCanon lists graph-backed alternatives at awesome-AutoML alternatives and Awesome-AI-Data-Guided-Projects alternatives (awesome-AutoML markdown twin, Awesome-AI-Data-Guided-Projects markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, awesome-AutoML or Awesome-AI-Data-Guided-Projects?
- awesome-AutoML: Slowing. Awesome-AI-Data-Guided-Projects: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for awesome-AutoML and Awesome-AI-Data-Guided-Projects?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-AutoML trust report; Awesome-AI-Data-Guided-Projects trust report.