Chip Huyen writes about AI system design and bringing AI applications into production.
Made With ML
Made With ML offers lessons on designing, developing, deploying, and improving production machine learning applications.
About Made With ML
Made With ML provides lessons on designing, developing, deploying and iterating on production machine learning applications. Topics include product and systems design, data preparation and processing, model training, tracking, tuning, evaluation and serving, testing, versioning, and production work such as jobs, CI/CD workflows and monitoring.
It also lists a live cohort with live lessons and Q&A, GPU compute and community interaction. The site is part of Anyscale and describes its material for developers, graduates and product leaders.
Key features
- Product and systems design lessons for ML applications
- Data preparation, exploration, preprocessing and distributed processing lessons
- Model training, tracking, tuning, evaluation and serving lessons
- Code, data and model testing lessons
- Versioning lessons for reproducibility
- Production lessons covering jobs, CI/CD workflows and monitoring
Best for: Developers, recent graduates, and product leaders who want practical skills for production machine learning applications.
Good for
- Explains machine learning concepts from first principles before code
- Includes software engineering practices for developing and deploying models
- Covers scaling workloads and connecting MLOps components in an end-to-end system
Made With ML at a glance
- Website
- madewithml.com
- Category
- Education & Learning › AI Learning & Guides
- Type
- Online tool
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Good for
- Developers
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Made With ML FAQ
Who is Made With ML for?
All developers, college graduates learning practical industry skills, and product and leadership roles seeking a technical foundation for ML products.
Does the content apply beyond fine-tuning LLMs?
Yes. While one task involves fine-tuning an LLM, the material is described as extending to NLP, CV, time-series, regression to LLMs, tabular and text data, AWS and GCP, and local to distributed scale.
What does the live cohort include?
Live lessons and Q&A, compute with GPUs, and community interaction to cover the material in one day.
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