Showing 1-20 of 91 projects
Learn to build production-grade ML applications with code and best practices
Apache Airflow for workflow orchestration
Vector database for AI applications
Open-source data labeling tool for AI/ML projects
MLflow is an open-source platform for building, tracking, and deploying AI/ML models with end-to-end observability and evaluation tools.
Build and deploy AI services with cloud-native stack
Curated list of open source libraries for deploying, monitoring, and scaling machine learning in production
Taipy is a Python library that helps developers turn data and AI algorithms into production-ready web apps quickly.
End-to-end tutorials covering production-grade GenAI agents with reusable patterns and blueprints.
An open-source machine learning engineering reference with resources for training, deploying, and scaling AI models.
Argo Workflows is a powerful open-source workflow engine for Kubernetes, enabling complex data processing and machine learning pipelines.
Weaviate is an open-source vector database that combines vector search with structured filtering and scalability.
A lightweight AI agent trainer for building agentic AI models.
An open-source data orchestration platform for developing, running, and observing data pipelines and workflows.
An open-source AutoML toolkit for automating the machine learning lifecycle, including feature engineering, neural architecture search, and hyperparameter tuning.
A free MLOps course that covers machine learning model deployment and monitoring
A curated list of references for MLOps, the practice of managing and automating machine learning workflows.
Deploy open-source LLMs as OpenAI-compatible API endpoints using BentoML's model serving framework.
A Python library that helps ensure data quality and reliability through data profiling and testing.
Open-source stack for industrial-grade LLM applications, including LLM gateway, observability, optimization, evaluation, and experimentation.
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