surrogate-models
Hyperactive
| surrogate-models | Hyperactive | |
|---|---|---|
| 1 | 8 | |
| 0 | 492 | |
| - | - | |
| 0.0 | 7.7 | |
| about 3 years ago | 5 months ago | |
| Python | Python | |
| MIT License | MIT License |
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surrogate-models
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Gradient-Free-Optimizers A collection of modern optimization methods in Python
Yes it is quite easy to switch algorithms via the "gpr" parameter. You just have to write a wrapper class. I am currently working on a repository that discusses how to do that in detail: https://github.com/SimonBlanke/surrogate-models
Hyperactive
- Hyperactive Version 4.5 Released
- Hyperactive: An optimization and data collection toolbox for AutoML
- Hyperactive: Optimize computationally expensive models with powerful algorithms
- Show HN: Hyperactive – A highly versatile AutoML Toolbox
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Hyperactive – Easy Neural Architecture Search for Deep Learning in Python
Check out the Neural Architecture Search Tutorial here: https://nbviewer.jupyter.org/github/SimonBlanke/hyperactive-...
Neural Architecture Search is just one of many optimization applications you can work on with Hyperactive. Check out the examples in the official github repository: https://github.com/SimonBlanke/Hyperactive/tree/master/examp...
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Gradient-Free-Optimizers A collection of modern optimization methods in Python
Gradient-Free-Optimizers is a lightweight optimization package that serves as a backend for Hyperactive: https://github.com/SimonBlanke/Hyperactive
Hyperactive can do parallel computing with multiprocessing or joblib, or a custom wrapper-function.
What are some alternatives?
Gradient-Free-Optimizers - Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
mango - Parallel Hyperparameter Tuning in Python
BayesianOptimization - A Python implementation of global optimization with gaussian processes.
pybobyqa - Python-based Derivative-Free Optimization with Bound Constraints
optimization-tutorial - Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.
opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
OpenMetadata - Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
optuna-examples - Examples for https://github.com/optuna/optuna
anovos - Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark