LLM-powered multiagent persona simulation for imagination enhancement and business insights.
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Documentation for Miku, covering setup, features, and practical usage.
List of several machine learning libraries.
📦 Open-Source Models (via Nebius).
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Building AGI with our mission Intelligence with Everyone. Global leader in multi-modal models and AI-native products with over 200 million users.
Overview of MiniMax AI models and their capabilities.
Minion AI provides machine-learning models, research, training resources, or evaluation tools.
An asynchronous engine for continuous & autonomous machine learning, built for real-time usage.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Mistral provides conversational AI for questions, tasks, and general assistance.
Deep learning foundations and applications.
MITRE ATLAS™ provides machine-learning models, research, training resources, or evaluation tools.
A Julia package for fitting (statistical) mixed-effects models.
A Repository Containing Classification, Clustering, Regression, Recommender Notebooks with illustration to make them.
ML Resources supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
All-in-one web-based IDE specialized for machine learning and data science.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
ML-Ops provides machine-learning models, research, training resources, or evaluation tools.
Machine learning and numerical analysis tools for Node.js and the Browser!
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design.