Free MLOps course from DataTalks.Club
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Updated
Jun 5, 2024 - Jupyter Notebook
Free MLOps course from DataTalks.Club
Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
🐢 Open-Source Evaluation & Testing for LLMs and ML models
AI Observability & Evaluation
nannyml: post-deployment data science in python
Open-source observability for your LLM application, based on OpenTelemetry
⚓ Eurybia monitors model drift over time and securizes model deployment with data validation
MLOps workshop with Amazon SageMaker
Version, share, deploy, and monitor models.
Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in production.
Sister project to OpenLLMetry, but in Typescript. Open-source observability for your LLM application, based on OpenTelemetry
The official python package for NimbleBox. Exposes all APIs as CLIs and contains modules to make ML 🌸
A python library to send data to Arize AI!
Toolkit for evaluating and monitoring AI models in clinical settings
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀
[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes
MLOps for deploying a Credit Risk model
Newron is a data-centric ML platform to easily build, manage, deploy and continuously improve models through data driven development.
A modern, enterprise-ready business intelligence web application
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