ai-agent

awesome-production-machine-learning

Name: awesome-production-machine-learning
Author: EthicalML

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

21,000 stars+46★ this week2,613 forksUpdated 10/8/2026100% free · open source

What it does

A curated GitHub list of open‑source libraries for deploying, monitoring, versioning, and scaling production machine‑learning systems.

When to use it

•You need to choose production‑ready tooling (e.g., model serving, feature stores) for a new ML product.
•Your team is evaluating alternatives and wants a single source of vetted open‑source options.
•You want to quickly compare community‑maintained solutions before committing to a vendor.

Ready-to-paste prompt

grep -i "monitor" README.md | head -n 10   # shows the first 10 monitoring tools listed in the awesome list

Heads up: The repo is only a reference list; it does not provide any code to run—each linked library has its own dependencies, version constraints, and setup steps that you must follow separately.

Saves to your device

Use with Claude

New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

⚡ Runs out of the box

A prompt/skill package — nothing to install beyond adding it to your AI tool.

Try it instantly — no install

Claude Code

mkdir -p ~/.claude/skills/awesome-production-machine-learning && curl -fsSL https://workflowstacks.com/api/skills/awesome-production-machine-learning/claude-skill -o ~/.claude/skills/awesome-production-machine-learning/SKILL.md

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How awesome-production-machine-learning works

Codeflow

Free to inspect

Awesome-production-machine-learning is a documents-only repository (3 doc files) — something you read, not something you run. There is nothing to install. Last commit this month, MIT license.

Size

Documents only

3 documents · 35 min skim

Setup

Nothing to install

A guide / curated list. Just read it and follow the links.

Runs on

Nowhere — you read it

A reading resource, not a program.

Where to start reading

1
README.md
Start here — what it does and how to install it

What's in each folder

images/Images & static assets3 files

.github/CI / automation (GitHub Actions)2 files

READMECI checksMIT licenseUpdated this month