Comparison
awesome-automl-papers vs AI-For-Beginners
Verdict
Pick awesome-automl-papers when license: awesome-automl-papers is Apache-2.0, AI-For-Beginners is MIT; pick AI-For-Beginners when license: AI-For-Beginners is MIT, awesome-automl-papers is Apache-2.0.
Markdown twin · awesome-automl-papers alternatives · AI-For-Beginners alternatives
GraphCanon updated today
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Trust & integrity
| Signal | awesome-automl-papers | AI-For-Beginners |
|---|---|---|
| Maintenance | Dormant (760d since push) As of today · github_public_v1 | Very active (2d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | 3 low (3 low) As of today · osv@v1 |
Tagline
- awesome-automl-papers
- A curated list of automated machine learning papers, articles, tutorials, slides and projects
- AI-For-Beginners
- 12 Weeks, 24 Lessons, AI for All!
Stars
- awesome-automl-papers
- 4.2k
- AI-For-Beginners
- 52k
Forks
- awesome-automl-papers
- 680
- AI-For-Beginners
- 11k
Open issues
- awesome-automl-papers
- 2
- AI-For-Beginners
- 4
Language
- awesome-automl-papers
- -
- AI-For-Beginners
- Jupyter Notebook
Adopt for
- awesome-automl-papers
- -
- AI-For-Beginners
- -
Persona
- awesome-automl-papers
- -
- AI-For-Beginners
- -
Runtime
- awesome-automl-papers
- -
- AI-For-Beginners
- -
License
- awesome-automl-papers
- Apache-2.0
- AI-For-Beginners
- MIT
Last pushed
- awesome-automl-papers
- Jun 11, 2024
- AI-For-Beginners
- Jul 8, 2026
Categories
- awesome-automl-papers
- Computer Vision, Vector Databases
- AI-For-Beginners
- Computer Vision, Model Training, Vector Databases
Trust and health
Maintenance
- awesome-automl-papers
- Dormant (18%)
- AI-For-Beginners
- Very active (96%)
Days since push
- awesome-automl-papers
- 760d
- AI-For-Beginners
- 2d
Open issues (now)
- awesome-automl-papers
- 2
- AI-For-Beginners
- 4
Owner type
- awesome-automl-papers
- User
- AI-For-Beginners
- Organization
Security scan
- awesome-automl-papers
- No lockfile
- AI-For-Beginners
- 3 low (3 low)
Full report
- awesome-automl-papers
- Trust report
- AI-For-Beginners
- Trust report
Choose awesome-automl-papers if…
- License: awesome-automl-papers is Apache-2.0, AI-For-Beginners is MIT.
- Tags unique to awesome-automl-papers: automated-feature-engineering, automl, hyperparameter-optimization, neural-architecture-search.
- Leaner open-issue backlog (2).
When NOT to use awesome-automl-papers
- Last GitHub push was 760 days ago (dormant maintenance, Jun 11, 2024). Validate activity before betting a new project on awesome-automl-papers.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
Choose AI-For-Beginners if…
- License: AI-For-Beginners is MIT, awesome-automl-papers is Apache-2.0.
- Tags unique to AI-For-Beginners: ai, artificial-intelligence, cnn, computer-vision.
- Also covers Model Training.
When NOT to use AI-For-Beginners
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (hibayesian/awesome-automl-papers) · observed Jul 11, 2026
- GitHub forks (hibayesian/awesome-automl-papers) · observed Jul 11, 2026
- Last push (hibayesian/awesome-automl-papers) · observed Jun 11, 2024
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (microsoft/AI-For-Beginners) · observed Jul 11, 2026
- GitHub forks (microsoft/AI-For-Beginners) · observed Jul 11, 2026
- Last push (microsoft/AI-For-Beginners) · observed Jul 8, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-automl-papers 4.2k · AI-For-Beginners 52k (synced Jul 11, 2026).
Common questions
- What is the difference between awesome-automl-papers and AI-For-Beginners?
- awesome-automl-papers: A curated list of automated machine learning papers, articles, tutorials, slides and projects. AI-For-Beginners: 12 Weeks, 24 Lessons, AI for All!. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-automl-papers over AI-For-Beginners?
- Choose awesome-automl-papers over AI-For-Beginners when License: awesome-automl-papers is Apache-2.0, AI-For-Beginners is MIT; Tags unique to awesome-automl-papers: automated-feature-engineering, automl, hyperparameter-optimization, neural-architecture-search; Leaner open-issue backlog (2).
- When should I choose AI-For-Beginners over awesome-automl-papers?
- Choose AI-For-Beginners over awesome-automl-papers when License: AI-For-Beginners is MIT, awesome-automl-papers is Apache-2.0; Tags unique to AI-For-Beginners: ai, artificial-intelligence, cnn, computer-vision; Also covers Model Training.
- When should I avoid awesome-automl-papers?
- Last GitHub push was 760 days ago (dormant maintenance, Jun 11, 2024). Validate activity before betting a new project on awesome-automl-papers. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- When should I avoid AI-For-Beginners?
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- Is awesome-automl-papers or AI-For-Beginners more popular on GitHub?
- AI-For-Beginners has more GitHub stars (52,098 vs 4,152). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-automl-papers and AI-For-Beginners open source?
- Yes - both are open-source projects on GitHub (awesome-automl-papers: Apache-2.0, AI-For-Beginners: MIT).
- Where can I find alternatives to awesome-automl-papers or AI-For-Beginners?
- GraphCanon lists graph-backed alternatives at awesome-automl-papers alternatives and AI-For-Beginners alternatives (awesome-automl-papers markdown twin, AI-For-Beginners 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-papers or AI-For-Beginners?
- awesome-automl-papers: Dormant. AI-For-Beginners: Very active. 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-papers and AI-For-Beginners?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-automl-papers trust report; AI-For-Beginners trust report.