bayesian-optimization

Here are 396 public repositories matching this topic...

microsoft / nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Updated Oct 4, 2022
Python

automl / auto-sklearn

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Automated Machine Learning with scikit-learn

scikit-learn hyperparameter-optimization bayesian-optimization hyperparameter-tuning automl automated-machine-learning smac meta-learning hyperparameter-search metalearning

Updated Oct 7, 2022
Python

fmfn / BayesianOptimization

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A Python implementation of global optimization with gaussian processes.

python simple optimization gaussian-processes bayesian-optimization

Updated Aug 30, 2022
Python

scikit-optimize / scikit-optimize

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Sequential model-based optimization with a `scipy.optimize` interface

visualization machine-learning binder optimization scikit-learn scientific-visualization scientific-computing hyperparameter-optimization bayesopt bayesian-optimization hacktoberfest hyperparameter-tuning hyperparameter hyperparameter-search sequential-recommendation

Updated Aug 30, 2022
Python

modAL-python / modAL

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A modular active learning framework for Python

python machine-learning scikit-learn machine-learning-algorithms machine-learning-library machine-learning-api bayesian-optimization active-learning active-learning-module

Updated Aug 10, 2022
Python

krasserm / bayesian-machine-learning

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Notebooks about Bayesian methods for machine learning

machine-learning bayesian-methods gaussian-processes bayesian-optimization bayesian-machine-learning variational-autoencoder

Updated Jan 19, 2021
Jupyter Notebook

LiYangHart / Hyperparameter-Optimization-of-Machine-Learning-Algorithms

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Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

Updated Sep 22, 2022
Jupyter Notebook

SimonBlanke / Gradient-Free-Optimizers

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Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.

machine-learning optimization constrained-optimization hyperparameter-optimization meta-heuristic simulated-annealing hill-climbing bayesian-optimization nelder-mead random-search particle-swarm-optimization evolution-strategies blackbox-optimization gradient-free-optimization tree-of-parzen-estimator hyperactive

Updated Aug 29, 2022
Python

automl / SMAC3

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Sequential Model-based Algorithm Configuration

random-forest configuration hyperparameter-optimization bayesian-optimization hyperparameter-tuning automl automated-machine-learning hyperparameter-search bayesian-optimisation gaussian-process algorithm-configuration

Updated Oct 7, 2022
Python

automl / HpBandSter

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a distributed Hyperband implementation on Steroids

hyperparameter-optimization bayesian-optimization automl automated-machine-learning neural-architecture-search

Updated Apr 22, 2022
Python

chrisstroemel / Simple

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Experimental Global Optimization Algorithm

optimization hyperparameter-optimization global-optimization bayesian-optimization blackbox-optimization

Updated Jan 29, 2018
Python

EmuKit / emukit

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A Python-based toolbox of various methods in uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

python machine-learning emulation decision-making uncertainty-quantification sensitivity-analysis bayesian-optimization experimental-design bayesian-quadrature multi-fidelity