All repos — GH Trending Explorer

🦙 Integrating LLMs into structured NLP pipelines

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).

uxlfoundation / scikit-learn-intelex

Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

sebp / scikit-survival

Survival analysis built on top of scikit-learn

PrunaAI / pruna

Pruna is a model optimization framework built for developers, enabling you to deliver faster, more efficient models with minimal overhead.

nok / sklearn-porter

Transpile trained scikit-learn estimators to C, Java, JavaScript and others.

NabidAlam / road-to-machine-learning

A comprehensive, step-by-step guide to learning Machine Learning from absolute basics to advanced topics

modal-labs / modal-examples

Examples of programs built using Modal

PyDMD / PyDMD

Python Dynamic Mode Decomposition

automl / SMAC3

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

MyoHub / myosuite

MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.

qualcomm / ai-hub-models

Qualcomm® AI Hub Models is our collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.

python-adaptive / adaptive

:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions

HyperGAN / HyperGAN

Composable GAN framework with api and user interface

onnx / onnxmltools

ONNXMLTools enables conversion of models to ONNX

extropic-ai / thrml

Thermodynamic Hypergraphical Model Library in JAX

lhotse-speech / lhotse

Tools for handling multimodal data in machine learning projects.

huawei-noah / trustworthyAI

Trustworthy AI related projects

AdaptiveMotorControlLab / CEBRA

Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA

ndif-team / nnsight

The nnsight package enables interpreting and manipulating the internals of deep learned models.

fraunhoferportugal / tsfel

Time Series Feature Extraction Library (TSFEL): 60+ statistical, temporal, spectral and fractal features for time series classification, regression and signal processing in Python

Toni-SM / skrl

Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments

microsoft / TimeCraft

Official code for TimeCraft: A Time Series Generation Framework for Real-World Applications

microsoft / Biodiversity

Microsoft AI for Good Lab — Biodiversity research hub. Open-source AI models, edge devices, and tools for biodiversity monitoring and conservation. Your source for MegaDetector, SPARROW, PytorchWildlife, Bioacoustics, and more.

NeuroTechX / moabb

Mother of All BCI Benchmarks

process-intelligence-solutions / pm4py

Official public repository for PM4Py (Process Mining for Python) — an open-source library for exploring, analyzing, and optimizing business processes with Python.

google-research / morph-net

Fast & Simple Resource-Constrained Learning of Deep Network Structure

yueliu1999 / Awesome-Deep-Graph-Clustering

[IEEE T-KDE 2026] Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).

keras-team / keras-hub

Pretrained model hub for Keras 3.

mir-group / nequip

NequIP is a code for building E(3)-equivariant interatomic potentials

AgileRL / AgileRL

The complete post-training stack for LLMs, plus RL for any problem. SFT, DPO and multi-turn agentic RL, with evolutionary hyperparameter optimization built in.

atomistic-machine-learning / schnetpack

SchNetPack - Deep Neural Networks for Atomistic Systems

retentioneering / retentioneering-tools

Python toolkit, MCP server, and agent skills for reproducible, auditable clickstream and event log analytics. Helps AI agents, data scientists and analysts build, validate, and cross-check product analytics, quantitative UX, customer journeys, graph-based user flows, behavioral segmentation, A/B tests, process mining models, Markov chain simulation

IBM / differential-privacy-library

Diffprivlib: The IBM Differential Privacy Library

strands-agents / samples

Agent samples built using the Strands Agents SDK.

Project-MONAI / MONAILabel

MONAI Label is an intelligent open source image labeling and learning tool.

huggingface / dataset-viewer

Backend that powers the dataset viewer on Hugging Face dataset pages through a public API.

Natooz / MidiTok

MIDI / symbolic music tokenizers for Deep Learning models 🎶

mosecorg / mosec

A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine

SeldonIO / MLServer

An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more

stratosphereips / StratosphereLinuxIPS

Slips, a free software behavioral Python intrusion prevention system (IDS/IPS) that uses machine learning to detect malicious behaviors in the network traffic. Stratosphere Laboratory, AIC, FEL, CVUT in Prague.

nolabs-ai / deepfabric

Generate High-Quality Synthetics, Train, Measure, and Evaluate in a Single Pipeline

sbi-dev / sbi

sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you need fine-grained control or an easy-to-use interface, sbi has you covered.

LAMDA-Tabular / TALENT

A comprehensive toolkit and benchmark for tabular data learning, featuring 35+ deep methods, more than 10 classical methods, and 300 diverse tabular datasets.

optuna / optuna-examples

Examples for https://github.com/optuna/optuna

insight-platform / Savant

Python Computer Vision & Video Analytics Framework With Batteries Included

dipy / dipy

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.