100-Days-Of-ML-Code中文版
A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
A python library for self-supervised learning on images.
All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.
:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning
Unsupervised time series anomaly detection library
Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel XPU (CPU-only and CUDA also supported).
Composable GAN framework with api and user interface
[IEEE T-KDE 2026] Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
BFM_Zero: A Promptable Behavioral Foundation Model for Humanoid Control Using Unsupervised Reinforcement Learning
Perceptive behavioral foundation models for terrain-adaptive humanoid control: motion tracking, goal reaching, reward inference and teleoperation.
Annotation-free multi-animal direction estimation using self-supervised learning