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4 repositories tagged with mlops
Awesome Automated AI/ML: Your Curated Guide to AI/ML Automation Tools
Awesome Automated AI/ML is a comprehensive, curated list featuring over 300 tools for automating various aspects of AI and Machine Learning. It covers everything from hyperparameter optimization to autonomous AI agents, offering a dynamic resource for ML engineers, AI researchers, and product builders.
LangTest: A Comprehensive Library for Safe & Effective Language Models
LangTest is an open-source Python library dedicated to ensuring the safety and effectiveness of language models. It offers a comprehensive framework for testing model quality, covering robustness, bias, fairness, and accuracy across various NLP tasks and LLM providers. With LangTest, developers can generate and execute over 60 distinct test types with just one line of code, promoting responsible AI development.
Evidently: Open-Source ML and LLM Observability Framework
Evidently is an open-source Python library designed for evaluating, testing, and monitoring machine learning and large language model systems. It provides over 100 built-in metrics for various tasks, from data drift detection to LLM judges, supporting both tabular and text data. This framework helps ensure the quality and performance of AI-powered systems throughout their lifecycle.
Giskard-OSS: Open-Source Evaluation & Testing Library for LLM Agents
Giskard-OSS is an open-source Python library designed for evaluating and testing AI systems, particularly LLM-based applications and traditional ML models. It automatically detects performance, bias, and security issues, offering comprehensive tools for ensuring the reliability and safety of AI. The library includes a powerful RAG Evaluation Toolkit (RAGET) for in-depth assessment of Retrieval Augmented Generation applications.