--- title: "Made-With-ML vs Awesome-AI-Data-Guided-Projects" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/gokumohandas-made-with-ml-vs-youssefhosni-awesome-ai-data-guided-projects" tools: ["gokumohandas-made-with-ml", "youssefhosni-awesome-ai-data-guided-projects"] --- # Made-With-ML vs Awesome-AI-Data-Guided-Projects *GraphCanon updated Sep 20, 2026* ## Verdict Pick Made-With-ML if made-With-ML is about equipping developers with practical resources to design, develop, deploy and iterate on production-grade machine learning applications within their software engineering workflows; 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. [Made-With-ML](https://madewithml.com) reports 50k GitHub stars, 7.8k forks, and 25 open issues, last pushed Mar 4, 2026. [Awesome-AI-Data-Guided-Projects](https://github.com/youssefHosni/Awesome-AI-Data-Guided-Projects) has 723 stars, 151 forks, and 2 open issues, last pushed May 5, 2024. Figures are from public GitHub metadata via [Made-With-ML's repository](https://github.com/GokuMohandas/Made-With-ML) and [Awesome-AI-Data-Guided-Projects's repository](https://github.com/youssefHosni/Awesome-AI-Data-Guided-Projects). | | [Made-With-ML](/tools/gokumohandas-made-with-ml.md) | [Awesome-AI-Data-Guided-Projects](/tools/youssefhosni-awesome-ai-data-guided-projects.md) | | --- | --- | --- | | Tagline | Learn to develop, deploy and iterate on production-grade ML applications | A curated list of data science & AI guided projects for portfolio-building | | Stars | 49,547 | 723 | | Forks | 7,778 | 151 | | Open issues | 25 | 2 | | Language | Jupyter Notebook | - | | Adopt for | Made-With-ML is about equipping developers with practical resources to design, develop, deploy and iterate on production-grade machine learning applications within their software engineering workflows. | 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 | - | - | | Runtime | - | - | | License | MIT | 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. | | Categories | Developer Tools, Inference & Serving, Model Training | Developer Tools, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Made-With-ML](/tools/gokumohandas-made-with-ml.md) | [Awesome-AI-Data-Guided-Projects](/tools/youssefhosni-awesome-ai-data-guided-projects.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 199d | 847d | | Open issues (now) | 25 | 2 | | Stars delta | +473 (30d) | 0 (30d) | | Open issues delta | -1 (30d) | 0 (30d) | | Full report | [trust report](/tools/gokumohandas-made-with-ml/trust.md) | [trust report](/tools/youssefhosni-awesome-ai-data-guided-projects/trust.md) | ## Decision facts: Made-With-ML - **Requirements:** A foundational understanding of Python programming is required to fully benefit from the learning resources provided. - **Adopt for:** Made-With-ML is about equipping developers with practical resources to design, develop, deploy and iterate on production-grade machine learning applications within their software engineering workflows. ## Decision facts: Awesome-AI-Data-Guided-Projects - **Adopt for:** 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. - **License detail:** 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. ## Choose when ### Choose Made-With-ML if… - License: Made-With-ML is MIT, Awesome-AI-Data-Guided-Projects is GPL-3.0. - Requirements: A foundational understanding of Python programming is required to fully benefit from the learning resources provided.. - Tags unique to Made-With-ML: data-engineering, data-quality, data-science, distributed-ml. - Also covers Inference & Serving. - If you are looking for comprehensive tutorials that connect foundational ML concepts directly with hands-on coding practices using Python and PyTorch. ### Choose Awesome-AI-Data-Guided-Projects if… - License: Awesome-AI-Data-Guided-Projects is GPL-3.0, Made-With-ML is MIT. - Tags unique to Awesome-AI-Data-Guided-Projects: ai, computer-vision, datascience, llm. - Also covers LLM Frameworks. - You need guided projects to build conversational chatbot applications. ## When NOT to use Made-With-ML - If you are looking for a niche-focused tool that caters specifically to a particular machine learning framework other than PyTorch. - For developers who already have strong backgrounds in MLOps and require highly specialized tools for managing production-grade ML deployments without additional educational support. ## 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. ## Common questions ### What is the difference between Made-With-ML and Awesome-AI-Data-Guided-Projects? Made-With-ML: Learn to develop, deploy and iterate on production-grade ML applications. 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 Made-With-ML over Awesome-AI-Data-Guided-Projects? Choose Made-With-ML over Awesome-AI-Data-Guided-Projects when License: Made-With-ML is MIT, Awesome-AI-Data-Guided-Projects is GPL-3.0; Requirements: A foundational understanding of Python programming is required to fully benefit from the learning resources provided.; Tags unique to Made-With-ML: data-engineering, data-quality, data-science, distributed-ml; Also covers Inference & Serving; If you are looking for comprehensive tutorials that connect foundational ML concepts directly with hands-on coding practices using Python and PyTorch. ### When should I choose Awesome-AI-Data-Guided-Projects over Made-With-ML? Choose Awesome-AI-Data-Guided-Projects over Made-With-ML when License: Awesome-AI-Data-Guided-Projects is GPL-3.0, Made-With-ML is MIT; Tags unique to Awesome-AI-Data-Guided-Projects: ai, computer-vision, datascience, llm; Also covers LLM Frameworks; You need guided projects to build conversational chatbot applications. ### When should I avoid Made-With-ML? If you are looking for a niche-focused tool that caters specifically to a particular machine learning framework other than PyTorch. For developers who already have strong backgrounds in MLOps and require highly specialized tools for managing production-grade ML deployments without additional educational support. ### 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 Made-With-ML or Awesome-AI-Data-Guided-Projects more popular on GitHub? Made-With-ML has more GitHub stars (49,547 vs 723). Stars measure visibility, not whether either tool fits your constraints. ### Are Made-With-ML and Awesome-AI-Data-Guided-Projects open source? Yes - both are open-source projects on GitHub (Made-With-ML: MIT, Awesome-AI-Data-Guided-Projects: GPL-3.0). ### Where can I find alternatives to Made-With-ML or Awesome-AI-Data-Guided-Projects? GraphCanon lists graph-backed alternatives at [Made-With-ML alternatives](/tools/gokumohandas-made-with-ml/alternatives) and [Awesome-AI-Data-Guided-Projects alternatives](/tools/youssefhosni-awesome-ai-data-guided-projects/alternatives) ([Made-With-ML markdown twin](/tools/gokumohandas-made-with-ml/alternatives.md), [Awesome-AI-Data-Guided-Projects markdown twin](/tools/youssefhosni-awesome-ai-data-guided-projects/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/gokumohandas-made-with-ml-vs-youssefhosni-awesome-ai-data-guided-projects.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Made-With-ML or Awesome-AI-Data-Guided-Projects? Made-With-ML: 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 Made-With-ML and Awesome-AI-Data-Guided-Projects? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Made-With-ML trust report](/tools/gokumohandas-made-with-ml/trust); [Awesome-AI-Data-Guided-Projects trust report](/tools/youssefhosni-awesome-ai-data-guided-projects/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=gokumohandas-made-with-ml`](/api/graphcanon/graph?tool=gokumohandas-made-with-ml) - 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/_