Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

Frouros: an open-source Python library for drift detection in machine learning systems.

🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 11 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴

😎 A curated list of awesome MLOps tools

Machine Learning Engineering Open Book

Leverage Metaflow, PyTorch, AWS S3, Elasticsearch, FastAPI and Docker to create a production-ready facial recognition solution. It demonstrates the practical use of deep metric learning to recognize previously unseen faces without prior training.

Having fun with MLOPS: Wine Stuff

This project aims to apply MLOps techniques to deploy a machine learning model through an API constructed with FastAPI. We utilize Poetry for dependency management and Docker for containerization, ensuring the code is modular, organized 📐, and maintainable 🛠️.

End-to-end MLOps Using MLflow for ML lifecycle, including data validation, processing, model training, evaluation, validation and deployment

Flower Classification Web Application (Built with Flask)

A framework for forecasting stock prices with emphasis on Machine Learning best practices.

The project comprises a real-time tweets data pipeline, a sentimental analysis of the tweets module, and a Slack bot to post the tweets' sentiments. The project uses SentimentIntensityAnalyzer from the VaderSentiment library. The analyzer gives positive, negative, and compound scores for small texts (such as tweets in this case). The real-time d…

This repository contains examples of using various libraries/tools for MLOps.

An cryptocurrency trading bot that uses automated machine learning for decision making to maximize returns.

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms