Hyperactive
optuna-examples
| Hyperactive | optuna-examples | |
|---|---|---|
| 8 | 2 | |
| 490 | 596 | |
| - | 3.5% | |
| 7.7 | 8.7 | |
| 5 months ago | 6 days 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.
optuna-examples
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[D]How to optimize an ANN?
Check out the examples for Optuna, a popular hyper parameter tuning package. It has examples for most popular ML frameworks including Xgboost, so you can see how it compares to an ANN framework like Keras or PyTorch.
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Data Scientists are dying out
That's still regular ML because you are in charge of the features. Optuna might make your life easier though: https://github.com/optuna/optuna-examples/blob/main/xgboost/xgboost_simple.py
What are some alternatives?
mango - Parallel Hyperparameter Tuning in Python
tqdm - :zap: A Fast, Extensible Progress Bar for Python and CLI
pybobyqa - Python-based Derivative-Free Optimization with Bound Constraints
optuna - A hyperparameter optimization framework
opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python
OpenMetadata - Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
SMAC3 - SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
optimization-tutorial - Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
anovos - Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.