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

20,861 stars2,590 forksUpdated 8/12/2026100% free · open source

What it does

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

Install / run

git clone https://github.com/EthicalML/awesome-production-machine-learning.git

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.

Quick start

1cd awesome-production-machine-learning && less README.md # open the list in your terminal
2Scroll to the section you need (e.g., "Model Serving") and copy the GitHub link of a library you like.
3Follow the linked library’s own installation guide (e.g., `pip install torchserve` for TorchServe).
4Add the chosen library to your project’s `requirements.txt` or `environment.yml` so it’s reproducible.
5Bookmark the README or fork the repo to keep your own curated version of the list.

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

Topics

awesome

awesome-list

data-mining

deep-learning

explainability

interpretability

large-scale-machine-learning

large-scale-ml

machine-learning

machine-learning-operations

ml-operations

ml-ops

mlops

privacy-preserving

privacy-preserving-machine-learning

privacy-preserving-ml

production-machine-learning

production-ml

responsible-ai

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