Hyperactive
opytimizer
| Hyperactive | opytimizer | |
|---|---|---|
| 8 | 7 | |
| 490 | 594 | |
| - | - | |
| 7.7 | 5.5 | |
| 5 months ago | 4 months ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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
-
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...
-
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.
opytimizer
-
[P] Opytimizer: A Nature-Inspired Python Optimizer
We do have a Simulated Annealing version designed to work with the library's structure: https://github.com/gugarosa/opytimizer/blob/master/opytimizer/optimizers/science/sa.py
-
Opytimizer: A Nature-Inspired Python Optimizer
Opytimizer: A Nature-Inspired Python Optimizer
Thanks mate! That would be a great addition indeed. We do have some examples over https://github.com/gugarosa/opytimizer/tree/master/examples/..., but they are not clearly depicted as the README would be. Thanks a lot!!
-
Gradient-Free-Optimizers A collection of modern optimization methods in Python
There's also Opytimizer [0] for almost every metaheuristic optimization algorithm under the Sun.
[0] https://github.com/gugarosa/opytimizer
What are some alternatives?
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.
OpenMetadata - Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
Gradient-Free-Optimizers - Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
optuna-examples - Examples for https://github.com/optuna/optuna
sqpdfo - Sequential-Quadratic-Programming Derivative-Free Optimization
flaxOptimizers - A collection of optimizers, some arcane others well known, for Flax.
anovos - Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark
lion-pytorch - 🦁 Lion, new optimizer discovered by Google Brain using genetic algorithms that is purportedly better than Adam(w), in Pytorch