Deep Learning
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An end-to-end open source platform for machine learning with a comprehensive ecosystem of tools and libraries.
An end-to-end open source platform for machine learning with a comprehensive ecosystem of tools and libraries.
A model-definition framework for state-of-the-art machine learning models across text, vision, audio, and multimodal tasks.
A model-definition framework for state-of-the-art machine learning models across text, vision, audio, and multimodal tasks.
A Python package for tensor computation with GPU acceleration and dynamic neural networks built on a tape-based autograd system.
An open-source library with over 2500 optimized algorithms for real-time computer vision and machine learning.
Open Source Computer Vision Library providing real-time image processing and AI capabilities.
A repository of state-of-the-art model implementations and examples built with TensorFlow, demonstrating best practices for research and production.
A repository of state-of-the-art model implementations and examples built with TensorFlow, demonstrating best practices for machine learning.
A comprehensive open-source guide covering prompt engineering techniques, papers, notebooks, and resources for LLMs, RAG, and AI agents.
A curated list of awesome machine learning frameworks, libraries, and software organized by programming language.
A curated list of awesome machine learning frameworks, libraries, and software organized by programming language.
A latent text-to-image diffusion model that generates detailed images from text prompts, running on GPUs with at least 10GB VRAM.
A collection of 60+ annotated PyTorch implementations of deep learning papers with side-by-side explanatory notes.
A multi-backend deep learning framework that enables effortless model development across JAX, TensorFlow, PyTorch, and OpenVINO.
A cutting-edge framework for training and deploying state-of-the-art YOLO models for object detection, segmentation, classification, and pose estimation.
A state-of-the-art PyTorch-based computer vision model for object detection, segmentation, and classification.
A simple Python library and CLI tool for facial recognition, detection, and feature manipulation using dlib's deep learning models.
A deep learning toolkit for Text-to-Speech generation with pretrained models in over 1100 languages and tools for training.
Transform Python scripts into interactive web apps for data dashboards, reports, and chat apps in minutes.
A comprehensive collection of TensorFlow tutorials and examples for beginners, covering both TF v1 and v2 with clear explanations.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Build and share machine learning web apps and demos in Python with minimal code.
A unified deep learning system for efficient large-scale model training and inference with advanced parallelism strategies.
A curated reading roadmap of foundational and state-of-the-art deep learning papers for newcomers and researchers.
A comprehensive collection of PyTorch image models, layers, utilities, and training scripts for computer vision research and applications.
Cross-platform framework for building customizable on-device machine learning pipelines for live and streaming media.
A PyTorch-based platform for state-of-the-art object detection, segmentation, and visual recognition tasks.
A fast open framework for deep learning with a focus on expression, speed, and modularity.
Real-time multi-person keypoint detection library for body, face, hands, and foot estimation.
A modular PyTorch library for state-of-the-art diffusion models to generate images, audio, and 3D molecular structures.
A visualizer for neural network, deep learning, and machine learning models across multiple frameworks.
A collection of concise PyTorch tutorials for deep learning researchers, with most models implemented in under 30 lines of code.
Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility and transparency.
A deep learning framework to pretrain and finetune any AI model on any hardware with zero code changes.
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