20 Open Source Tools I Recommend to Build, Share, and Run AI Projects

Data Science And Machine Learning Developer Tools Workflow Automation

Streamlit Landing Page
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Streamlit

Turn python scripts into beautiful ML tools
Pricing:
- Open Source
Streamlit is an open source platform that turns your Python scripts into shareable web apps in minutes with just a few lines of code. These interactive web apps are often the demo apps for most ML projects. The most fascinating thing about this platform is that it requires no front-end or back-end experience. Moreover, Streamlit lets you create these sites without HTML, CSS, or JavaScript, without defining routes and focusing on handling HTTP requests.

#Developer Tools #Content Creators #Application And Data 209 social mentions
OpenCV Landing Page
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OpenCV

OpenCV is the world's biggest computer vision library
Pricing:
- Open Source
OpenCV is an open-source computer vision and machine learning software library that allows users to perform various ML tasks, from processing images and videos to identifying objects, faces, or handwriting. Besides object detection, this platform can also be used for complex computer vision tasks like Geometry-based monocular or stereo computer vision.

#Data Science And Machine Learning #Data Science Tools #Computer Vision 59 social mentions
Metaflow Landing Page
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Metaflow

Framework for real-life data science; build, improve, and operate end-to-end workflows.
Pricing:
- Open Source
Metaflow is an open source framework developed at Netflix for building and managing ML, AI, and data science projects. This tool addresses the issue of deploying large data science applications in production by allowing developers to build workflows using their Python API, explore with notebooks, test, and quickly scale out to the cloud. ML experiments and workflows can also be tracked and stored on the platform.

#Workflow Automation #Developer Tools #DevOps Tools 14 social mentions
Kedro Landing Page
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Kedro

An open-source framework for data science code
Pricing:
- Open Source
Kedro is an ML development framework that brings data science projects from pilot development to production by creating reproducible, maintainable, and modular data science code. Kedro has a data catalog for data handling, support pipeline building, and a standardized template for code maintainability and consistency to effectively do this. Its data catalog uses lightweight data connectors to manage and track datasets. This allows you to use the same pipeline to build multiple production-level codes across your system.

#Data Science And Machine Learning #Data Pipelines #Python Web Framework 2 social mentions