syne-tune
SMAC3
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| syne-tune | SMAC3 | |
|---|---|---|
| 1 | 2 | |
| 363 | 1,008 | |
| 1.4% | 3.9% | |
| 8.1 | 3.2 | |
| 8 days ago | 6 days ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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syne-tune
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Amazon AI Researchers Open-Source ‘Syne Tune’: A Novel Python Library For Distributed HPO With An Emphasis On Enabling Reproducible Machine Learning Research
Continue reading | Checkout the paper, github
SMAC3
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[D]How to optimize an ANN?
You can use Optuna, SMAC or hyperopt
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Finding the optimal parameter
Apart from the aforementioned comments noting that this is an optimization problem, ready-to-use python libraries for this kind of problem (accounting for evaluation time) include http://hyperopt.github.io/hyperopt/, https://github.com/automl/SMAC3, or https://www.ray.io/ray-tune
What are some alternatives?
auto-sklearn - Automated Machine Learning with scikit-learn
hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
optuna - A hyperparameter optimization framework
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
optuna-examples - Examples for https://github.com/optuna/optuna
mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
OCTIS - OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)