Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Open source software that helps you create and deploy high-frequency crypto trading bots
A hyperparameter optimization framework
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
- machine-learning
- experiment-track
- deep-learning
- keras
Fast and Accurate ML in 3 Lines of Code
The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.
- cloud-computing
- deep-learning
- gpu
- hyperparameter-tuning
🐚 Python-powered shell. Full-featured, cross-platform and AI-friendly.
- xonsh
- devops
- iterm2
- data-engineering
Automated Machine Learning with scikit-learn
- automl
- scikit-learn
- automated-machine-learning
- hyperparameter-optimization
Distributed Asynchronous Hyperparameter Optimization in Python
- hacktoberfest
Free open source crypto trading bot to automate AI, Grid, DCA and TradingView strategies on Binance, Hyperliquid and 15+ exchanges, with a simple interface.
- trading-bot
- python
- bitcoin
- ai-trading
关掉国产安卓手机系统里的广告、热搜、资讯推荐和营销推送。不 root，可还原，支持 AI 智能体一键执行。
Automatic architecture search and hyperparameter optimization for PyTorch
- automl
- deep-learning
- tabular-data
- pytorch
Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.
- kv-cache
- llm-inference
- local-llm
- quantization
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
- hyperopt
- keras
- hyperparameter-optimization
Hyper-parameter optimization for sklearn
Hyperparameter Experiments with TensorFlow and Keras
- deep-learning
- keras
- keras-tensorflow
- hyperparameter-optimization
Hypercorn is an ASGI and WSGI Server based on Hyper libraries and inspired by Gunicorn.
- asyncio
- python
- http-server
- asgi
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
- bayesian-optimization
- bayesian-optimisation
- hyperparameter-optimization
- hyperparameter-tuning
Library for Fast and Flexible Human Pose Estimation
- tensorlayer
- tensorflow
- openpose
- pose-estimation
EL2 hypervisor and toolchain that boots macOS on the ASUS A16 (Snapdragon X2 Elite), with an Adreno Metal/IOGPU stack
An autoML framework & toolkit for machine learning on graphs.
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.
- pipeline
- pipeline-framework
- machine-learning
- deep-learning
Rebuild a reference video as an editable HyperFrames project, compare the match against the original, and export an MP4.
- hyperframes
- motion-graphics
- python
- video