diffrax: a JAX-based library for autodifferentiable and GPU-capable numerical differential equation solvers
A JAX-based library for numerical differential equation solvers that is autodifferentiable and GPU-capable, supporting ODEs, SDEs, and CDEs.
SimpleHTR: a handwritten text recognition system that converts images of words and text lines into digital text
A TensorFlow-based handwritten text recognition system that converts images of single words or text lines into digital text using CNN and LSTM layers.
xlstm: a recurrent neural network architecture that extends LSTM to compete with Transformers in language modeling
A new Recurrent Neural Network architecture that extends LSTM to compete with Transformers and State Space Models, featuring a 7B parameter language model for efficient inference.
GeneticAlgorithmPython: an intuitive genetic algorithm library for optimizing machine learning models and complex functions
A Python library for building genetic algorithms to optimize mathematical functions and machine learning models, with native support for Keras and PyTorch.
raster-vision: a geospatial computer vision framework for building ML models on satellite and aerial imagery
A Python library and low-code framework for building computer vision models on satellite, aerial, and drone imagery using PyTorch.
audiomentations: a fast and easy-to-use audio data augmentation library for deep learning
A Python library for audio data augmentation that provides a wide variety of transforms to make audio deep learning models more robust for real-world use.
torchio: a PyTorch-based toolkit for preprocessing and augmenting 3D medical images with domain-specific artifacts
A Python library for PyTorch that provides tools for the efficient loading, preprocessing, and augmentation of 3D medical images.
synthetic-data-generator: a privacy-preserving tabular data generator supporting GANs, LLMs, and billion-scale datasets
A specialized framework for generating high-quality, privacy-preserving synthetic tabular data using statistical models, GANs, and LLMs.
torchmetrics: a scalable PyTorch metrics library for distributed training and evaluation
A collection of over 100 PyTorch metrics implementations that automate accumulation and synchronization across distributed devices to reduce boilerplate in ML pipelines.
kompute: a cross-vendor GPU compute framework for high-performance acceleration across different graphics card brands
A cross-vendor GPU compute framework based on Vulkan that enables high-performance acceleration for machine learning and data processing across AMD, NVIDIA, and Qualcomm hardware.
deepdetect: a deep learning runtime and REST server for unified training and inference across multiple modalities
A deep learning runtime and REST server that provides a unified API for training and inference across images, text, and tabular data.
kuberay: a Kubernetes operator for managing the lifecycle of Ray clusters, jobs, and services
A Kubernetes operator that simplifies the deployment, scaling, and management of Ray applications for distributed AI workloads.
voxelmorph: a learning-based framework for deformable medical image registration and alignment
A general-purpose library for learning-based image registration and deformation modelling, primarily used for aligning medical imaging scans.
Papers-in-100-Lines-of-Code: minimal implementations of over 60 influential AI research papers each under 100 lines of code
A collection of minimal implementations of over 60 influential AI and machine learning research papers, each written in 100 lines of code or fewer.
leptonai: a Python library and CLI for managing and operating AI workloads on NVIDIA DGX Cloud Lepton
A Python library and CLI for the NVIDIA DGX Cloud Lepton platform, allowing users to deploy and manage AI endpoints, batch jobs, and clusters.
AIF360: an extensible toolkit for detecting and mitigating algorithmic bias in machine learning models
An extensible open-source library for Python and R that provides metrics and algorithms to detect and mitigate algorithmic bias in machine learning models.
DeepCamera: an open-source AI camera platform with autonomous hardware-aware skill deployment and local VLM analysis
An open-source AI camera platform that enables local deployment of VLM scene analysis and object detection skills with autonomous, hardware-aware installation.
AlphaTree-graphic-deep-neural-network: a visual learning roadmap for deep learning models linking academic papers to practical code implementations
A structured visual roadmap and resource collection that helps developers transition to AI application engineering by linking papers, code, and diagrams for deep learning models.
dm-haiku: a neural network library for JAX that enables object-oriented model definition
A neural network library for JAX that enables object-oriented model definition while maintaining compatibility with JAX's pure function transformations.
SDV: a machine learning library for generating and evaluating privacy-preserving tabular synthetic data
A Python library for creating tabular synthetic data using machine learning to emulate real-world patterns while maintaining privacy.
scikit-llm: a scikit-learn compatible wrapper for integrating LLMs into text analysis pipelines
A library that integrates Large Language Models like ChatGPT into scikit-learn, enabling enhanced text analysis tasks such as zero-shot classification.
reinforcement-learning: a collection of standalone PyTorch implementations of core reinforcement learning algorithms
A collection of easy-to-read, standalone PyTorch implementations of core reinforcement learning algorithms, from basic Grid World to deep RL for Atari games.
segment-geospatial: a geospatial segmentation tool that adapts the Segment Anything Model for remote sensing imagery
A Python package that adapts the Segment Anything Model (SAM) for geospatial data, enabling easy segmentation of satellite imagery using text, points, or boxes.
neuralforecast: a user-friendly collection of state-of-the-art neural time-series forecasting models
A library of over 30 state-of-the-art neural forecasting models providing a user-friendly, scikit-learn style API for high-performance time-series prediction.
FLAML: a fast and economical AutoML engine for model selection and hyperparameter optimization
A lightweight Python library for efficient automated machine learning (AutoML) and hyperparameter tuning to find high-quality models with minimal computational resources.
probability: a library for probabilistic reasoning and statistical analysis with deep network integration
A library for probabilistic reasoning and statistical analysis that integrates probabilistic methods with deep networks using TensorFlow or JAX.
autotrain-advanced: a no-code solution for training and deploying state-of-the-art machine learning models
A no-code tool for training and deploying machine learning models, supporting a wide range of tasks from LLM fine-tuning to image classification.
watermark-removal: a machine learning based image inpainting tool for removing watermarks
A machine learning project that uses image inpainting to remove watermarks from images, creating seamless, high-quality results.
dm_control: a physics-based simulation stack for Reinforcement Learning and continuous control using MuJoCo
A software stack for physics-based simulation and Reinforcement Learning environments powered by the MuJoCo physics engine.
Flux.jl: a pure-Julia machine learning framework with native GPU and automatic differentiation support
A pure-Julia machine learning framework that provides lightweight abstractions for building and training models using native GPU and automatic differentiation support.
ignite: a high-level training and evaluation library for PyTorch that replaces boilerplate loops with a flexible event-driven system
A high-level library for PyTorch that simplifies neural network training and evaluation through a flexible engine and event-driven system.
djl: an engine-agnostic Java framework for building, training, and deploying deep learning models
An engine-agnostic Java framework for deep learning that allows Java developers to build, train, and deploy models using a native Java experience.
pytorch-forecasting: a high-level deep learning framework for interpretable multi-horizon time series forecasting
A PyTorch-based package for time series forecasting that provides a high-level API and state-of-the-art deep learning architectures like Temporal Fusion Transformers and N-BEATS.
grobid: a machine learning library for extracting and structuring bibliographic data from scientific PDFs
A machine learning library that parses raw PDF scientific publications into structured XML/TEI documents for high-scale bibliographic data extraction.
gluonts: a probabilistic time series modeling library based on PyTorch
A Python package for probabilistic time series modeling that uses deep learning and PyTorch to generate forecasts with uncertainty intervals.
SynapseML: a scalable machine learning library for building distributed ML pipelines on Apache Spark
An open-source library built on Apache Spark that provides scalable, distributed APIs for machine learning tasks like text analytics, vision, and anomaly detection.
sahi: a vision library for performing sliced inference to detect small objects in large images
A lightweight vision library that enables sliced inference to detect small objects in large-scale images across various popular object detection frameworks.
tch-rs: Rust bindings for the PyTorch C++ API providing tensor operations and neural network training
Rust bindings for the PyTorch C++ API (libtorch), enabling the use of PyTorch's tensor operations and neural network training in Rust.
flashlight: a high-performance C++ machine learning library with JIT kernel compilation and native multi-domain apps
A fast, flexible C++ machine learning library providing a core tensor interface and neural network tools for high-performance AI research across speech, vision, and text.
composer: a deep learning training library for scaling PyTorch workflows across GPU clusters
A PyTorch-based deep learning library that simplifies distributed training at scale, providing tools for memory optimization and algorithmic speedups to reduce training time and cost.
mlpack: a fast header-only C++ machine learning library with multi-language bindings
A fast, header-only C++ machine learning library that provides a wide array of ML methods and functions with bindings for Python, Julia, Go, and R.
NN-SVG: a parametric generator for publication-ready neural network architecture schematics
A parametric tool for creating publication-ready neural network architecture diagrams in SVG format, eliminating the need to draw them manually.
DALI: a GPU-accelerated data loading and pre-processing library that eliminates CPU bottlenecks in deep learning pipelines
A GPU-accelerated library for data loading and pre-processing that removes CPU bottlenecks in deep learning pipelines for image, video, and audio data.
tsai: a deep learning library for time series and sequential data with a vast collection of SOTA models
A state-of-the-art deep learning library built on PyTorch and fastai for time series tasks including classification, regression, and forecasting.
serving: a high-performance production system for managing and serving versioned machine learning model inference
A high-performance serving system for machine learning models designed to manage model lifetimes and provide versioned inference via gRPC and HTTP in production environments.
smile: a high-performance JVM machine learning framework with integrated LLM inference and an agentic data science IDE
A comprehensive, high-performance machine learning framework for the JVM that provides tools for classical ML, deep learning, LLM inference, and an agentic data science IDE.
flower: a framework-agnostic system for building and scaling federated AI
A framework for building federated AI systems that enables decentralized model training across various ML frameworks and devices.
autograd: an automatic differentiation library for native Python and NumPy code
A library that automatically differentiates native Python and NumPy code to enable efficient gradient-based optimization.
stanza: a multilingual Python NLP library with neural pipelines for 60+ languages and specialized biomedical models
A Python NLP library from Stanford that provides accurate neural processing tools for 60+ languages and a wrapper for the Java Stanford CoreNLP software.
modelscope: a unified Model-as-a-Service framework for seamless inference and fine-tuning of diverse AI models
A Model-as-a-Service (MaaS) platform and library that provides a unified interface for discovering, inferring, and fine-tuning hundreds of state-of-the-art AI models across multiple domains.