#28 · Primary category: Education & Research
Made-With-ML
Learn how to develop, deploy and iterate on production-grade ML applications.
Project last updated:03/04/26
GitHub Stars
49.3K
Forks
7.7K
Contributors
1
License
MIT
Why we included this project
Made With ML is a free, project-based course that walks you through the entire machine learning lifecycle, starting from a Jupyter notebook experiment and ending with a deployed, monitored service. It's not a library you drop into your stack; the payoff comes from following the lessons and adapting the code to your own project. For developers and small teams trying to understand how data pipelines, training, tuning, serving, and CI/CD fit together, it offers a realistic blueprint you can actually follow. The material also spends time on MLOps details like testing, logging, and versioning, which are easy to overlook when you learn ML in isolation. If you're ready to move past toy models and ship something real, this is a practical map of the territory.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
prompts.chat
f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.
JavaGuide
Java Interview & Backend General Interview Guide, covering computer fundamentals, databases, distributed systems, high concurrency, system design, and AI application development.
system-prompts-and-models-of-ai-tools
A curated collection of system prompts, internal tools, and AI models from popular AI assistants and coding agents.
30-seconds-of-code
Coding articles to level up your development skills
generative-ai-for-beginners
21 Lessons, Get Started Building with Generative AI