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Tensors and Dynamic neural networks in Python with strong GPU acceleration
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.
Fast and Accurate ML in 3 Lines of Code
Translate manga/image 一键翻译各类图片内文字 https://cotrans.touhou.ai/ (no longer working)
AutoML library for deep learning
Efficiently computes derivatives of NumPy code.
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
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.
Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
Automatic architecture search and hyperparameter optimization for PyTorch
Deep probabilistic analysis of single-cell and spatial omics data
Hyperparameter Experiments with TensorFlow and Keras
World's first general purpose 3D object detection codebse.
MLBox is a powerful Automated Machine Learning python library.
An autoML framework & toolkit for machine learning on graphs.
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
TensorFlow Implementation for Computing a Semantically Segmented Bird's Eye View (BEV) Image Given the Images of Multiple Vehicle-Mounted Cameras.
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
Maze Applied Reinforcement Learning Framework
Automated 3D cell detection in very large images