A collection of machine learning examples and tutorials.
🧙 Build, run, and manage data pipelines for integrating and transforming data.
BoxMOT: Pluggable Python and C++ SOTA multi-object tracking modules with support for axis-aligned and oriented bounding boxes
Uniform Manifold Approximation and Projection
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
Flexible and powerful framework for managing multiple AI agents and handling complex conversations
Official Python client library for kubernetes
Efficiently computes derivatives of NumPy code.
A specialized Claude Code workspace for creating long-form, SEO-optimized blog content for any business. This system helps you research, write, analyze, and optimize content that ranks well and serves your target audience.
Very efficient backup system based on the git packfile format, providing fast incremental saves and global deduplication (among and within files, including virtual machine images). Please post problems or patches to the mailing list for discussion (see the end of the README below).
Flower: A Friendly Federated AI Framework
Native MLX runtime for Laya typed decision models — 7–14 ms short decisions on M3 Max. No text generation, PyTorch, or cloud API.
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
🌊 Online machine learning in Python
Democratizing Reinforcement Learning for LLMs
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
NVIDIA cuML: GPU-Accelerated Machine Learning
Machine Learning and Computer Vision Engineer - Technical Interview Questions
🤗 AutoTrain Advanced
Post-training with Tinker
A Python package for segmenting geospatial data with the Segment Anything Model (SAM)
Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.
Superfast AI decision making and intelligent processing of multi-modal data.
DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
WebApps in pure Python. No JavaScript, HTML and CSS needed
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Evaluation and Tracking for LLM Experiments and AI Agents
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Seamlessly integrate LLMs into scikit-learn.
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
JAX-based neural network library
The machine learning toolkit for time series analysis in Python
🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.
:sunglasses: A curated list of robotics libraries and software
Universal memory layer for AI Agents. It provides scalable, extensible, and interoperable memory storage and retrieval to streamline AI agent state management for next-generation autonomous systems.
A simple tool to update bib entries with their official information (e.g., DBLP or the ACL anthology).
Data manipulation and transformation for audio signal processing, powered by PyTorch
POT : Python Optimal Transport
A Pythonic framework to simplify AI service building
Images to inference with no labeling (use foundation models to train supervised models).
🧠 Make your agents learn from experience. Now available as a hosted solution at kayba.ai
Single-cell analysis in Python. Scales to >100M cells.
Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.
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Message Passing Neural Networks for Molecule Property Prediction
LinuxCNC controls CNC machines. It can drive milling machines, lathes, 3d printers, laser cutters, plasma cutters, robot arms, hexapods, and more.
🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
An open-source framework for machine learning and other computations on decentralized data.
Medical imaging processing for AI applications.
SDG is a specialized framework designed to generate high-quality structured tabular data.
Optax is a gradient processing and optimization library for JAX.
Master the fundamentals of machine learning, deep learning, and mathematical optimization by building key concepts and models from scratch using Python.
A Python package to assess and improve fairness of machine learning models.
FAIR Chemistry's library of machine learning methods for chemistry
A unified orchestration layer for heterogeneous AI compute. It standardizes how to manage compute and run training and inference on GPU clouds, Kubernetes, VMs, or bare-metal clusters.
A library for training and deploying machine learning models on Amazon SageMaker
开放式的缠论python实现框架,支持形态学/动力学买卖点分析计算,多级别K线联立,区间套策略,可视化绘图,多种数据接入,策略开发,交易系统对接;