General technology for enabling AI capabilities w/ LLMs and MLLMs.
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Integrate LLM technology quickly and easily into your apps.
LLM-powered multiagent persona simulation for imagination enhancement and business insights.
List of several machine learning libraries.
📦 Open-Source Models (via Nebius).
MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.
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.
An asynchronous engine for continuous & autonomous machine learning, built for real-time usage.
Intuitive convenience tooling for lightning-fast, efficient development and ensuring quality in LLM-based applications.
Deep learning foundations and applications.
C, C++, and Python tools for named entity recognition and relation extraction.
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.
Version and deploy your ML models following GitOps principles.
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.