--- title: "awesome-automl-papers vs AI-For-Beginners" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hibayesian-awesome-automl-papers-vs-microsoft-ai-for-beginners" tools: ["hibayesian-awesome-automl-papers", "microsoft-ai-for-beginners"] --- # awesome-automl-papers vs AI-For-Beginners *GraphCanon updated Jul 11, 2026* ## 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. [awesome-automl-papers](https://github.com/hibayesian/awesome-automl-papers) reports 4.2k GitHub stars, 680 forks, and 2 open issues, last pushed Jun 11, 2024. [AI-For-Beginners](https://github.com/microsoft/AI-For-Beginners) has 52k stars, 11k forks, and 4 open issues, last pushed Jul 8, 2026. Figures are from public GitHub metadata via [awesome-automl-papers's repository](https://github.com/hibayesian/awesome-automl-papers) and [AI-For-Beginners's repository](https://github.com/microsoft/AI-For-Beginners). | | [awesome-automl-papers](/tools/hibayesian-awesome-automl-papers.md) | [AI-For-Beginners](/tools/microsoft-ai-for-beginners.md) | | --- | --- | --- | | Tagline | A curated list of automated machine learning papers, articles, tutorials, slides and projects | 12 Weeks, 24 Lessons, AI for All! | | Stars | 4,152 | 52,098 | | Forks | 680 | 10,536 | | Open issues | 2 | 4 | | Language | - | Jupyter Notebook | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Computer Vision, Vector Databases | Computer Vision, Model Training, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-automl-papers](/tools/hibayesian-awesome-automl-papers.md) | [AI-For-Beginners](/tools/microsoft-ai-for-beginners.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 760d | 2d | | Open issues (now) | 2 | 4 | | Owner type | User | Organization | | Security scan | No lockfile | 3 low (3 low) | | Full report | [trust report](/tools/hibayesian-awesome-automl-papers/trust.md) | [trust report](/tools/microsoft-ai-for-beginners/trust.md) | ## Choose when ### 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). ### 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 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 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. ## 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](/tools/hibayesian-awesome-automl-papers/alternatives) and [AI-For-Beginners alternatives](/tools/microsoft-ai-for-beginners/alternatives) ([awesome-automl-papers markdown twin](/tools/hibayesian-awesome-automl-papers/alternatives.md), [AI-For-Beginners markdown twin](/tools/microsoft-ai-for-beginners/alternatives.md)), 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](/compare/hibayesian-awesome-automl-papers-vs-microsoft-ai-for-beginners.md) 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](/tools/hibayesian-awesome-automl-papers/trust); [AI-For-Beginners trust report](/tools/microsoft-ai-for-beginners/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hibayesian-awesome-automl-papers`](/api/graphcanon/graph?tool=hibayesian-awesome-automl-papers) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_