Integrate LLM technology quickly and easily into your apps.
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LLM-powered multiagent persona simulation for imagination enhancement and business insights.
List of several machine learning libraries.
An asynchronous engine for continuous & autonomous machine learning, built for real-time usage.
Deep learning foundations and applications.
C, C++, and Python tools for named entity recognition and relation extraction.
A Julia package for fitting (statistical) mixed-effects models.
ML Resources supports machine learning models, deployment, inspection, datasets, or AI development workflows.
All-in-one web-based IDE specialized for machine learning and data science.
Machine learning and numerical analysis tools for Node.js and the Browser!
500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design.
Friendly machine learning for the web!
A set of functions to support the development of machine learning algorithms.
A Julia machine learning framework.
A simple Machine Learning Framework written in Swift. Currently features Simple Linear Regression, Polynomial Regression, and Ridge Regression.
No need to keep checking your training, just one import line and you'll know the second it's done.
A scalable C++ machine learning library.
MLX is an array framework for machine learning on Apple silicon, developed by Apple machine learning research.
A library consisting of useful tools for data science and machine learning tasks.
MMDeploy supports machine learning models, deployment, inspection, datasets, or AI development workflows.
A modular active learning framework for Python, built on top of scikit-learn.
Visual testing tool for MCP servers.
ModelFox is a platform for managing and deploying machine learning models.
Models.dev supports machine learning models, deployment, inspection, datasets, or AI development workflows.