Hyperactive
optimization-tutorial
| Hyperactive | optimization-tutorial | |
|---|---|---|
| 8 | 1 | |
| 490 | 17 | |
| - | - | |
| 7.7 | 0.0 | |
| 5 months ago | about 2 years ago | |
| Python | Python | |
| MIT License | MIT License |
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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.
optimization-tutorial
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Gradient-Free-Optimizers A collection of modern optimization methods in Python
I will look into this algorithm. Thanks for the suggestion. I have some basic explanations of the optimization techniques and their parameters in a separate repository: https://github.com/SimonBlanke/optimization-tutorial
But there is still a lot of work to be done.
What are some alternatives?
mango - Parallel Hyperparameter Tuning in Python
opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
pybobyqa - Python-based Derivative-Free Optimization with Bound Constraints
BayesianOptimization - A Python implementation of global optimization with gaussian processes.
Gradient-Free-Optimizers - Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
OpenMetadata - Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
surrogate-models - A collection of surrogate models for sequence model based optimization techniques
optuna-examples - Examples for https://github.com/optuna/optuna
sigopt-server - Open Source version of SigOpt API, performing hyperparameter optimization and visualization
anovos - Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark