ai-agent

Boost AI with awesome-machine-learning

Name: Boost AI with awesome-machine-learning
Author: josephmisiti

Get top Machine Learning frameworks for your startup, curated for founders like you, with 73k+ GitHub stars

beginner⏱ 5 minutes💵 Free

74,148 stars15,621 forksPythonHealth Score 9/10Updated 8/24/2026100% free · open source

What it is

Use this to quickly find the best Machine Learning tools and libraries curated by the community.

What you can make with it

You can make informed decisions when choosing the right Machine Learning tools for your project.

How it helps

It helps you save time searching for tools and libraries, instead of scouring online forums and documentation.

Real use case example

"A founder, Emma, needs to choose a reliable NLP library for her startup's chatbot. She uses this skill to browse the curated list of popular libraries and selects the best one for her project. In just 30 minutes, Emma finds the perfect library and has her chatbot up and running."

If you're new

Pick this up when you're just starting to learn about Machine Learning and want to explore different tools and libraries.

If you're senior

Use this when you're already familiar with Machine Learning and want to stay up-to-date with the latest tools and libraries.

Common confusion cleared up

Don't confuse this skill with a full-featured documentation site; it's a curated list meant to save time, not provide in-depth guides.

Best inside these AI tools

Any AI Client

Pairs with

Claude APINotion database

Why we list it on WorkflowStacks: As a comprehensive list, it's a valuable resource for our marketplace of AI tools and saves users from searching elsewhere.

What it does

Awesome-machine-learning provides a curated list of Machine Learning frameworks, libraries, and software for researchers and developers to explore and utilize in their projects.

Install / run

Since awesome-machine-learning is a GitHub repository, the first step is to clone it using the command: git clone https://github.com/josephmisiti/awesome-machine-learning.git

When to use it

•When searching for a comprehensive list of Machine Learning resources
•When looking for inspiration for new project ideas using Machine Learning
•When trying to find alternative libraries or frameworks for a specific Machine Learning task

Quick start

1Clone the repository using the command: git clone https://github.com/josephmisiti/awesome-machine-learning.git
2Navigate into the cloned repository: cd awesome-machine-learning
3Open the README.md file to explore the curated list of Machine Learning resources
4Browse through the categorized lists of frameworks, libraries, and software to find relevant resources for your project
5Use the provided links to visit the official websites or documentation of the resources that interest you

Ready-to-paste prompt

To find a specific type of Machine Learning library, use the command: grep 'library_name' README.md, replacing 'library_name' with the actual name of the library you are looking for

Heads up: The repository is primarily a curated list of resources and does not include any executable code or dependencies, so users should be aware that they will need to visit the individual resource websites to access and utilize the actual libraries or frameworks.

Saves to your device

How Boost AI with awesome-machine-learning works

Codeflow

Free to inspect

Boost AI with awesome-machine-learning is mostly documents (8 doc files, 1 small script) — something you read, not something you run. There is nothing to install. Last commit this month, Other license.

Size

Mostly documents

8 documents · 1 small script · 55 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.

Python 100%

Where to start reading