🐢 Open-Source Evaluation & Testing for LLMs and ML models
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Updated
May 30, 2024 - Python
🐢 Open-Source Evaluation & Testing for LLMs and ML models
Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
Free MLOps course from DataTalks.Club
AI Observability & Evaluation
Open-source observability for your LLM application, based on OpenTelemetry
nannyml: post-deployment data science in python
This repository contains the notes, practice and sample outputs, homeworks, etc, from DataTalks.Club's MLOps Zoomcamp 2024 Cohort
Toolkit for evaluating and monitoring AI models in clinical settings
Sister project to OpenLLMetry, but in Typescript. Open-source observability for your LLM application, based on OpenTelemetry
A python library to send data to Arize AI!
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.
Solutions to the MLOps Zoomcamp course
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀
Aditi @ Building Production Grade LLMs - * Thank you AI community for visiting my repository - Stay tuned for awesome Dev-ops AI Learning Resources ** ** If you find the repository useful please give it a star - Thank you for visiting my repository - Happy Learning **
⚓ Eurybia monitors model drift over time and securizes model deployment with data validation
Version, share, deploy, and monitor models.
"1 config, 1 command from Jupyter Notebook to serve Millions of users", Full-stack On-Premises MLOps system for Computer Vision from Data versioning to Model monitoring and drift detection.
MLOps workshop with Amazon SageMaker
Experiments with Model Training, Deployment & Monitoring
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