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bayesian-optimization

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nni

microsoft / nni

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

python data-science machine-learning deep-learning neural-network tensorflow machine-learning-algorithms pytorch distributed feature-extraction hyperparameter-optimization feature-engineering nas bayesian-optimization automl automated-machine-learning model-compression neural-architecture-search deep-neural-network automated-feature-engineering
  • Updated Jul 2, 2021
  • Python
Gradient-Free-Optimizers

SimonBlanke / Gradient-Free-Optimizers

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Grid search variant

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SimonBlanke
SimonBlanke commented Mar 9, 2021

I think it would be useful to have a grid search optimizer in this package. But its implementation would probably be quite different from other ones (sklearn, ...).

The requirements are:

  • The grid search has to stop after n_iter instead of searching the entire search space
  • The positions should not be precalculated at the beginning of the optimization (i have concerns about memory load).
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enhancement good first issue help wanted

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)

machine-learning deep-learning random-forest optimization svm genetic-algorithm machine-learning-algorithms hyperparameter-optimization artificial-neural-networks grid-search tuning-parameters knn bayesian-optimization hyperparameter-tuning random-search particle-swarm-optimization hpo python-examples python-samples hyperband
  • Updated Jun 21, 2021
  • Jupyter Notebook
Hyperactive

SimonBlanke / Hyperactive

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A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

python metadata data-science machine-learning deep-learning optimization scikit-learn parallel-computing keras pytorch artificial-intelligence xgboost hyperparameter-optimization feature-engineering bayesian-optimization automated-machine-learning parameter-tuning neural-architecture-search meta-learning meta-heuristics
  • Updated Jul 2, 2021
  • Python

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