Comparison
ai-getting-started vs Made-With-ML
Verdict
Pick ai-getting-started if ai-getting-started is a TypeScript-based JavaScript AI tool tailored for weekend projects, offering everything from model implementation to deployment configurations; 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.
Markdown twin · ai-getting-started alternatives · Made-With-ML alternatives
GraphCanon updated Sep 20, 2026
12views this month
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Trust & integrity
| Signal | ai-getting-started | Made-With-ML |
|---|---|---|
| Maintenance | Dormant (759d since push) As of Sep 20, 2026 · github_public_v1 | Slowing (199d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | Published findings As of Jul 15, 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
- ai-getting-started
- A Javascript AI getting started stack for weekend projects
- Made-With-ML
- Learn to develop, deploy and iterate on production-grade ML applications
Stars
- ai-getting-started
- 4.1k
- Made-With-ML
- 50k
Forks
- ai-getting-started
- 659
- Made-With-ML
- 7.8k
Open issues
- ai-getting-started
- 16
- Made-With-ML
- 25
Language
- ai-getting-started
- TypeScript
- Made-With-ML
- Jupyter Notebook
Adopt for
- ai-getting-started
- ai-getting-started is a TypeScript-based JavaScript AI tool tailored for weekend projects, offering everything from model implementation to deployment configurations.
- 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.
Persona
- ai-getting-started
- -
- Made-With-ML
- -
Runtime
- ai-getting-started
- -
- Made-With-ML
- -
License
- ai-getting-started
- MIT
- Made-With-ML
- MIT
Last pushed
- ai-getting-started
- Aug 21, 2024
- Made-With-ML
- Mar 4, 2026
Categories
- ai-getting-started
- Developer Tools, Model Training, Vector Databases
- Made-With-ML
- Developer Tools, Inference & Serving, Model Training
Trust and health
Maintenance
- ai-getting-started
- Dormant (18%)
- Made-With-ML
- Slowing (36%)
Days since push
- ai-getting-started
- 759d
- Made-With-ML
- 199d
Open issues (now)
- ai-getting-started
- 16
- Made-With-ML
- 25
Stars delta
- ai-getting-started
- +1 (30d)
- Made-With-ML
- +473 (30d)
Open issues delta
- ai-getting-started
- 0 (30d)
- Made-With-ML
- -1 (30d)
Owner type
- ai-getting-started
- Organization
- Made-With-ML
- User
Full report
- ai-getting-started
- Trust report
- Made-With-ML
- Trust report
Choose ai-getting-started if…
- ai-getting-started is primarily TypeScript; Made-With-ML is Jupyter Notebook.
- Tags unique to ai-getting-started: deployment, image models, javascript, text models.
- Also covers Vector Databases.
- ai-getting-started ships Docker support for self-hosted deployment.
- * Use this tool if you are already familiar with or prefer working in TypeScript and want an easy entry point into AI project development.
When NOT to use ai-getting-started
- * If your focus is on developing large-scale, production-level applications, this tool may not offer the necessary scalability features.
- * Not suitable if you require highly customized vector stores or specific AI model training environments beyond what the package provides as it focuses more on a general setup.
Choose Made-With-ML if…
- Made-With-ML is primarily Jupyter Notebook; ai-getting-started is TypeScript.
- 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, deep-learning.
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (a16z-infra/ai-getting-started) · observed Sep 20, 2026
- GitHub forks (a16z-infra/ai-getting-started) · observed Sep 20, 2026
- Last push (a16z-infra/ai-getting-started) · observed Aug 21, 2024
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- 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 on cards: ai-getting-started 4.1k · Made-With-ML 50k (synced Sep 20, 2026).
Common questions
- What is the difference between ai-getting-started and Made-With-ML?
- ai-getting-started: A Javascript AI getting started stack for weekend projects. Made-With-ML: Learn to develop, deploy and iterate on production-grade ML applications. See the comparison table for live GitHub stats and shared categories.
- When should I choose ai-getting-started over Made-With-ML?
- Choose ai-getting-started over Made-With-ML when ai-getting-started is primarily TypeScript; Made-With-ML is Jupyter Notebook; Tags unique to ai-getting-started: deployment, image models, javascript, text models; Also covers Vector Databases; ai-getting-started ships Docker support for self-hosted deployment; * Use this tool if you are already familiar with or prefer working in TypeScript and want an easy entry point into AI project development.
- When should I choose Made-With-ML over ai-getting-started?
- Choose Made-With-ML over ai-getting-started when Made-With-ML is primarily Jupyter Notebook; ai-getting-started is TypeScript; 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, deep-learning; 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 avoid ai-getting-started?
- * If your focus is on developing large-scale, production-level applications, this tool may not offer the necessary scalability features. * Not suitable if you require highly customized vector stores or specific AI model training environments beyond what the package provides as it focuses more on a general setup.
- 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.
- Is ai-getting-started or Made-With-ML more popular on GitHub?
- Made-With-ML has more GitHub stars (49,547 vs 4,142). Stars measure visibility, not whether either tool fits your constraints.
- Are ai-getting-started and Made-With-ML open source?
- Yes - both are open-source projects on GitHub (ai-getting-started: MIT, Made-With-ML: MIT).
- Where can I find alternatives to ai-getting-started or Made-With-ML?
- GraphCanon lists graph-backed alternatives at ai-getting-started alternatives and Made-With-ML alternatives (ai-getting-started markdown twin, Made-With-ML 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, ai-getting-started or Made-With-ML?
- ai-getting-started: Dormant. Made-With-ML: Slowing. 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 ai-getting-started and Made-With-ML?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ai-getting-started trust report; Made-With-ML trust report.