ML Engineering for Developers Who've Only Ever Trained Models

What it does

Made With ML is an open-source curriculum and reference codebase that covers the full machine learning lifecycle, from experimental design to deployed service. It begins with a Jupyter notebook for interactive exploration, then refactors the same logic into a modular Python package handling data, training, tuning, evaluation, and serving. The goal is to teach the software engineering rigor—testing, logging, versioning, and CI/CD—that turns a one-off experiment into a reliable production system.

The interesting bit

The course treats the notebook as a rough draft, not a final deliverable. It uses Ray and the Anyscale platform to scale the same Python code from a laptop to a distributed cluster, and it stitches together MLOps pieces like MLflow tracking without asking you to rewrite your pipeline for every new environment.

Key highlights

• End-to-end scope: covers design, development, deployment, and iteration rather than stopping at model accuracy.
• Notebook-to-scripts pipeline: core logic starts in madewithml.ipynb and graduates to clean, importable modules.
• Distributed by default: leverages Ray for data processing, distributed training, hyperparameter tuning, and model serving.
• MLOps wiring: integrates experiment tracking via MLflow and emphasizes CI/CD workflows for continuous training and deployment.
• Audience-agnostic: explicitly targets software engineers, data scientists, recent graduates, and even product managers.

Caveats

• The course defaults to the Anyscale platform and Ray; local execution works but is explicitly described as slower.
• It is educational material, not a reusable library you can drop into an existing codebase.
• The README frequently steers readers toward paid Anyscale compute and live cohort sign-ups.

Verdict

A solid bookmark for developers who want to understand how ML systems are actually built, shipped, and maintained. Less useful if you need a standalone framework or a deep dive into a specific modeling technique.