A collection of machine learning optimization toolkits.
A simple introduction for Hyperparameter Optimization.
⭐ AutoKeras
🧰 AutoKeras: An AutoML system based on Keras.
⭐ KerasTuner
🧰 KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algorithms built-in.
⭐ Talos
🧰 Hyperparameter Optimization for Keras, TensorFlow and PyTorch.
⭐ AutoGluon
🧰 AutoGluon: AutoML for Text, Image, and Tabular Data.
⭐ Ray Tune
🧰 Tune is a library for hyperparameter tuning at any scale.
⭐ Optuna
🧰A hyperparameter optimization framework.
⭐ BOHB
🧰 BOHB: Robust and Efficient Hyperparameter Optimization at Scale.
⭐ HpBandSter
🧰 A distributed Hyperband implementation on Steroids.
⭐ Hyperopt
🧰 Distributed Asynchronous Hyper-parameter Optimization.
⭐ HiPlot
🧰 High dimensional Interactive Plotting.
⭐ Polyaxon
🧰 A platform for building, training, and monitoring large scale deep learning applications.
⭐ Bayesian Optimization
🧰 Pure Python implementation of bayesian global optimization with gaussian processes.
⭐ SHERPA
🧰 SHERPA: A Python Hyperparameter Optimization Library.
⭐ Scikit-optimize
🧰 Sequential model-based optimization.
⭐ GPyOpt
🧰 A Python open-source library for Bayesian Optimization(Maintenance terminated).
Reference: 10 Hyperparameter optimization frameworks (Towards Data Science).
