Comparison
Failed-ML vs AI-For-Beginners
Verdict
Pick Failed-ML when tags unique to Failed-ML: classification, data-engineering, data-quality, data-science; pick AI-For-Beginners when tags unique to AI-For-Beginners: cnn, gan, machine-learning, microsoft-for-beginners.
Markdown twin · Failed-ML alternatives · AI-For-Beginners alternatives
GraphCanon updated today
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Trust & integrity
| Signal | Failed-ML | AI-For-Beginners |
|---|---|---|
| Maintenance | Dormant (757d 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
- Failed-ML
- Compilation of high-profile real-world examples of failed machine learning projects
- AI-For-Beginners
- 12 Weeks, 24 Lessons, AI for All!
Stars
- Failed-ML
- 753
- AI-For-Beginners
- 52k
Forks
- Failed-ML
- 51
- AI-For-Beginners
- 11k
Open issues
- Failed-ML
- 0
- AI-For-Beginners
- 4
Language
- Failed-ML
- -
- AI-For-Beginners
- Jupyter Notebook
Adopt for
- Failed-ML
- -
- AI-For-Beginners
- -
Persona
- Failed-ML
- -
- AI-For-Beginners
- -
Runtime
- Failed-ML
- -
- AI-For-Beginners
- -
License
- Failed-ML
- MIT
- AI-For-Beginners
- MIT
Last pushed
- Failed-ML
- Jun 14, 2024
- AI-For-Beginners
- Jul 8, 2026
Categories
- Failed-ML
- Computer Vision, LLM Frameworks, Model Training
- AI-For-Beginners
- Computer Vision, Model Training, Vector Databases
Trust and health
Maintenance
- Failed-ML
- Dormant (18%)
- AI-For-Beginners
- Very active (96%)
Days since push
- Failed-ML
- 757d
- AI-For-Beginners
- 2d
Open issues (now)
- Failed-ML
- 0
- AI-For-Beginners
- 4
Owner type
- Failed-ML
- User
- AI-For-Beginners
- Organization
Security scan
- Failed-ML
- No lockfile
- AI-For-Beginners
- 3 low (3 low)
Full report
- Failed-ML
- Trust report
- AI-For-Beginners
- Trust report
Choose Failed-ML if…
- Tags unique to Failed-ML: classification, data-engineering, data-quality, data-science.
- Also covers LLM Frameworks.
- Leaner open-issue backlog (0).
When NOT to use Failed-ML
- Last GitHub push was 758 days ago (dormant maintenance, Jun 14, 2024). Validate activity before betting a new project on Failed-ML.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Choose AI-For-Beginners if…
- Tags unique to AI-For-Beginners: cnn, gan, machine-learning, microsoft-for-beginners.
- Also covers Vector Databases.
- More GitHub stars (52k vs 753) - visibility, not fit.
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 (kennethleungty/Failed-ML) · observed Jul 11, 2026
- GitHub forks (kennethleungty/Failed-ML) · observed Jul 11, 2026
- Last push (kennethleungty/Failed-ML) · observed Jun 14, 2024
- License file (MIT) · 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: Failed-ML 753 · AI-For-Beginners 52k (synced Jul 11, 2026).
Common questions
- What is the difference between Failed-ML and AI-For-Beginners?
- Failed-ML: Compilation of high-profile real-world examples of failed machine learning 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 Failed-ML over AI-For-Beginners?
- Choose Failed-ML over AI-For-Beginners when Tags unique to Failed-ML: classification, data-engineering, data-quality, data-science; Also covers LLM Frameworks; Leaner open-issue backlog (0).
- When should I choose AI-For-Beginners over Failed-ML?
- Choose AI-For-Beginners over Failed-ML when Tags unique to AI-For-Beginners: cnn, gan, machine-learning, microsoft-for-beginners; Also covers Vector Databases; More GitHub stars (52k vs 753) - visibility, not fit.
- When should I avoid Failed-ML?
- Last GitHub push was 758 days ago (dormant maintenance, Jun 14, 2024). Validate activity before betting a new project on Failed-ML. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- 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 Failed-ML or AI-For-Beginners more popular on GitHub?
- AI-For-Beginners has more GitHub stars (52,098 vs 753). Stars measure visibility, not whether either tool fits your constraints.
- Are Failed-ML and AI-For-Beginners open source?
- Yes - both are open-source projects on GitHub (Failed-ML: MIT, AI-For-Beginners: MIT).
- Where can I find alternatives to Failed-ML or AI-For-Beginners?
- GraphCanon lists graph-backed alternatives at Failed-ML alternatives and AI-For-Beginners alternatives (Failed-ML 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, Failed-ML or AI-For-Beginners?
- Failed-ML: 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 Failed-ML and AI-For-Beginners?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Failed-ML trust report; AI-For-Beginners trust report.