1.ray-project / ray
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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14 repositories by Attention Score · Aug 5, 2026 – Nov 2, 2026 (UTC)
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
A hyperparameter optimization framework
Fast and Accurate ML in 3 Lines of Code
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Automated Machine Learning with scikit-learn
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Sequential model-based optimization with a `scipy.optimize` interface
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
Hyperparameter Experiments with TensorFlow and Keras
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
Bayesian Optimization using GPflow