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Awesome List
A curated list of awesome Machine Learning frameworks, libraries and software.
GitHub stars and default-branch commits for josephmisiti/awesome-machine-learning.
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Promote a GitHub repo at the top of Awesome repository list views for 7 days.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Data Apps & Dashboards for Python. No JavaScript Required.
Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and more. Simple declarative configs with command line and CI/CD integration. Used by OpenAI and Anthropic.
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/
Build, run and scale AI agents like API and microservices - observable,auditable and identity-aware from day one.
ML powered analytics engine for outlier detection and root cause analysis.