Comparison
Made-With-ML vs Awesome-AI-Data-Guided-Projects
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.
Markdown twin · Made-With-ML alternatives · Awesome-AI-Data-Guided-Projects alternatives
GraphCanon updated Sep 20, 2026
13views this month
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Trust & integrity
| Signal | Made-With-ML | Awesome-AI-Data-Guided-Projects |
|---|---|---|
| Maintenance | Slowing (199d since push) As of Sep 20, 2026 · github_public_v1 | Dormant (847d since push) As of Aug 31, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Aug 31, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- 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
Stars
- Made-With-ML
- 50k
- Awesome-AI-Data-Guided-Projects
- 723
Forks
- Made-With-ML
- 7.8k
- Awesome-AI-Data-Guided-Projects
- 151
Open issues
- Made-With-ML
- 25
- Awesome-AI-Data-Guided-Projects
- 2
Language
- Made-With-ML
- Jupyter Notebook
- Awesome-AI-Data-Guided-Projects
- -
Adopt for
- Made-With-ML
- 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
- 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
- Made-With-ML
- -
- Awesome-AI-Data-Guided-Projects
- -
Runtime
- Made-With-ML
- -
- Awesome-AI-Data-Guided-Projects
- -
License
- Made-With-ML
- MIT
- Awesome-AI-Data-Guided-Projects
- 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.
Last pushed
- Made-With-ML
- Mar 4, 2026
- Awesome-AI-Data-Guided-Projects
- May 5, 2024
Categories
- Made-With-ML
- Developer Tools, Inference & Serving, Model Training
- Awesome-AI-Data-Guided-Projects
- Developer Tools, LLM Frameworks, Model Training
Trust and health
Maintenance
- Made-With-ML
- Slowing (36%)
- Awesome-AI-Data-Guided-Projects
- Dormant (18%)
Days since push
- Made-With-ML
- 199d
- Awesome-AI-Data-Guided-Projects
- 847d
Open issues (now)
- Made-With-ML
- 25
- Awesome-AI-Data-Guided-Projects
- 2
Stars delta
- Made-With-ML
- +473 (30d)
- Awesome-AI-Data-Guided-Projects
- 0 (30d)
Open issues delta
- Made-With-ML
- -1 (30d)
- Awesome-AI-Data-Guided-Projects
- 0 (30d)
OSV dependency advisories
- Made-With-ML
- Published findings
- Awesome-AI-Data-Guided-Projects
- No lockfile (source not queried)
Full report
- Made-With-ML
- Trust report
- Awesome-AI-Data-Guided-Projects
- Trust report
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.
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.
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (GokuMohandas/Made-With-ML) · observed Sep 20, 2026
- GitHub forks (GokuMohandas/Made-With-ML) · observed Sep 20, 2026
- Last push (GokuMohandas/Made-With-ML) · observed Mar 4, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (youssefHosni/Awesome-AI-Data-Guided-Projects) · observed Sep 20, 2026
- GitHub forks (youssefHosni/Awesome-AI-Data-Guided-Projects) · observed Sep 20, 2026
- Last push (youssefHosni/Awesome-AI-Data-Guided-Projects) · observed May 5, 2024
- License file (GPL-3.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Made-With-ML 50k · Awesome-AI-Data-Guided-Projects 723 (synced Sep 20, 2026).
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 and Awesome-AI-Data-Guided-Projects alternatives (Made-With-ML markdown twin, Awesome-AI-Data-Guided-Projects 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, 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; Awesome-AI-Data-Guided-Projects trust report.