Popular GitHub Repositories for Data Engineering

Learn how to design, develop, deploy and iterate on production-grade ML applications.

The Open Source Feature Store for AI/ML

Spreadsheet with AI, Code, Connections

Learn how to design, develop, deploy and iterate on production-grade ML applications.

A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine

Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.

MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.

A Data Engineering & Machine Learning Knowledge Hub

Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.

VectorFlow is a high volume vector embedding pipeline that ingests raw data, transforms it into vectors and writes it to a vector DB of your choice.

FeatHub - A stream-batch unified feature store for real-time machine learning

PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more

Construct a modern data stack and orchestration the workflows to create high quality data for analytics and ML applications.

An automatic ML model optimization tool.

An End to End GenAI Framework

Escola Livre de IA, Inteligência Artificial ao alcance de todos

A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.

Resources about data science, machine learning, deep learning, data engineering, and SQL.

Deep Neural Network architecture as a predictive optimal controller for {HVAC+Solar cell + battery} disturbance afflicted system vs classic Model Predictive Control

Materials for the Deploy and Monitor ML Pipelines with Python, Docker and GitHub Actions workshop at the PyData NYC 2024 conference