--- title: "awesome-generative-ai-guide vs ml-surveys" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aishwaryanr-awesome-generative-ai-guide-vs-eugeneyan-ml-surveys" tools: ["aishwaryanr-awesome-generative-ai-guide", "eugeneyan-ml-surveys"] --- # awesome-generative-ai-guide vs ml-surveys *GraphCanon updated Sep 20, 2026* ## Verdict Pick awesome-generative-ai-guide if awesome-generative-ai-guide is a curated repository for generative AI resources, including research updates, interview questions, and Jupyter notebooks, aimed at researchers and developers in the field of generative AI; pick ml-surveys if ml-surveys is a collection of detailed review papers summarizing advancements in various AI domains such as deep learning, NLP, CV, graphs, reinforcement learning, and recommendation systems. [awesome-generative-ai-guide](https://www.linkedin.com/in/areganti/) reports 29k GitHub stars, 6.0k forks, and 4 open issues, last pushed Sep 17, 2026. [ml-surveys](https://github.com/eugeneyan/ml-surveys) has 2.9k stars, 291 forks, and 2 open issues, last pushed Mar 17, 2023. Figures are from public GitHub metadata via [awesome-generative-ai-guide's repository](https://github.com/aishwaryanr/awesome-generative-ai-guide) and [ml-surveys's repository](https://github.com/eugeneyan/ml-surveys). | | [awesome-generative-ai-guide](/tools/aishwaryanr-awesome-generative-ai-guide.md) | [ml-surveys](/tools/eugeneyan-ml-surveys.md) | | --- | --- | --- | | Tagline | A one stop repository for generative AI research updates, interview resources, notebooks and much more! | Survey papers summarizing advances in various AI domains | | Stars | 29,463 | 2,903 | | Forks | 5,953 | 291 | | Open issues | 4 | 2 | | Language | HTML | - | | Adopt for | awesome-generative-ai-guide is a curated repository for generative AI resources, including research updates, interview questions, and Jupyter notebooks, aimed at researchers and developers in the field of generative AI. | ml-surveys is a collection of detailed review papers summarizing advancements in various AI domains such as deep learning, NLP, CV, graphs, reinforcement learning, and recommendation systems. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Computer Vision, Developer Tools, LLM Frameworks, Model Training | Computer Vision, Evaluation & Observability, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-generative-ai-guide](/tools/aishwaryanr-awesome-generative-ai-guide.md) | [ml-surveys](/tools/eugeneyan-ml-surveys.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 1283d | | Open issues (now) | 4 | 2 | | Stars delta | +692 (30d) | +1 (30d) | | Open issues delta | -1 (30d) | 0 (30d) | | Full report | [trust report](/tools/aishwaryanr-awesome-generative-ai-guide/trust.md) | [trust report](/tools/eugeneyan-ml-surveys/trust.md) | ## Decision facts: awesome-generative-ai-guide - **Adopt for:** awesome-generative-ai-guide is a curated repository for generative AI resources, including research updates, interview questions, and Jupyter notebooks, aimed at researchers and developers in the field of generative AI. ## Decision facts: ml-surveys - **Adopt for:** ml-surveys is a collection of detailed review papers summarizing advancements in various AI domains such as deep learning, NLP, CV, graphs, reinforcement learning, and recommendation systems. ## Choose when ### Choose awesome-generative-ai-guide if… - Tags unique to awesome-generative-ai-guide: awesome, awesome-list, generative-ai, interview-questions. - Also covers Developer Tools, LLM Frameworks. - Use awesome-generative-ai-guide when you need a comprehensive collection of resources for generative AI research, including updates and interview preparation materials. ### Choose ml-surveys if… - Tags unique to ml-surveys: computer-vision, deep-learning, embeddings, machine-learning. - Also covers Evaluation & Observability. - When you need comprehensive overviews and summaries of the latest research trends in multiple areas within machine learning ## When NOT to use awesome-generative-ai-guide - Do not use awesome-generative-ai-guide if you are seeking a platform for real-time collaboration on AI projects, as it primarily serves as a repository of static resources. - Avoid using this tool if you require a more specialized focus on a particular aspect of AI, such as reinforcement learning or natural language processing, as it is a broad overview and may not cover a ## When NOT to use ml-surveys - If you are seeking detailed technical details, original experiments, or specific algorithm implementations as ml-surveys focuses more on synthesis and summary - In cases where deep-dive analysis is required into a single niche topic, as ml-surveys provides broad overviews rather than in-depth coverage of individual niches ## Common questions ### What is the difference between awesome-generative-ai-guide and ml-surveys? awesome-generative-ai-guide: A one stop repository for generative AI research updates, interview resources, notebooks and much more!. ml-surveys: Survey papers summarizing advances in various AI domains. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-generative-ai-guide over ml-surveys? Choose awesome-generative-ai-guide over ml-surveys when Tags unique to awesome-generative-ai-guide: awesome, awesome-list, generative-ai, interview-questions; Also covers Developer Tools, LLM Frameworks; Use awesome-generative-ai-guide when you need a comprehensive collection of resources for generative AI research, including updates and interview preparation materials. ### When should I choose ml-surveys over awesome-generative-ai-guide? Choose ml-surveys over awesome-generative-ai-guide when Tags unique to ml-surveys: computer-vision, deep-learning, embeddings, machine-learning; Also covers Evaluation & Observability; When you need comprehensive overviews and summaries of the latest research trends in multiple areas within machine learning. ### When should I avoid awesome-generative-ai-guide? Do not use awesome-generative-ai-guide if you are seeking a platform for real-time collaboration on AI projects, as it primarily serves as a repository of static resources. Avoid using this tool if you require a more specialized focus on a particular aspect of AI, such as reinforcement learning or natural language processing, as it is a broad overview and may not cover a ### When should I avoid ml-surveys? If you are seeking detailed technical details, original experiments, or specific algorithm implementations as ml-surveys focuses more on synthesis and summary In cases where deep-dive analysis is required into a single niche topic, as ml-surveys provides broad overviews rather than in-depth coverage of individual niches ### Is awesome-generative-ai-guide or ml-surveys more popular on GitHub? awesome-generative-ai-guide has more GitHub stars (29,463 vs 2,903). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-generative-ai-guide and ml-surveys open source? Yes - both are open-source projects on GitHub (awesome-generative-ai-guide: MIT, ml-surveys: MIT). ### Where can I find alternatives to awesome-generative-ai-guide or ml-surveys? GraphCanon lists graph-backed alternatives at [awesome-generative-ai-guide alternatives](/tools/aishwaryanr-awesome-generative-ai-guide/alternatives) and [ml-surveys alternatives](/tools/eugeneyan-ml-surveys/alternatives) ([awesome-generative-ai-guide markdown twin](/tools/aishwaryanr-awesome-generative-ai-guide/alternatives.md), [ml-surveys markdown twin](/tools/eugeneyan-ml-surveys/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/aishwaryanr-awesome-generative-ai-guide-vs-eugeneyan-ml-surveys.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-generative-ai-guide or ml-surveys? awesome-generative-ai-guide: Very active. ml-surveys: 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-generative-ai-guide and ml-surveys? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-generative-ai-guide trust report](/tools/aishwaryanr-awesome-generative-ai-guide/trust); [ml-surveys trust report](/tools/eugeneyan-ml-surveys/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aishwaryanr-awesome-generative-ai-guide`](/api/graphcanon/graph?tool=aishwaryanr-awesome-generative-ai-guide) - 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/_