vizier
SpaceDrones
vizier | SpaceDrones | |
---|---|---|
5 | 1 | |
1,173 | 4 | |
0.7% | - | |
9.3 | 7.8 | |
1 day ago | 7 months ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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.
vizier
- [N] Google Open Sources Vizier, Hyperparameter + Blackbox Optimization Service at Scale
- Is there any premade evolutionary algorithm selecting optimal NN architectures in TensorFlow ?
- Google just open sourced its Vizier optimisation suite
- Python-based research interface for blackbox and hyperparameter optimization
SpaceDrones
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SpaceDrones: A simple learning environment for genetic optimization
Github: https://github.com/kaifishr/SpaceDrones
What are some alternatives?
mango - Parallel Hyperparameter Tuning in Python
RocketLander - A simple framework equipped with optimization algorithms, such as reinforcement learning, evolution strategies, genetic optimization, and simulated annealing, to enable an orbital rocket booster to land autonomously.
Gradient-Free-Optimizers - Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
GeneticAlgorithmPython - Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
keras-tuner - A Hyperparameter Tuning Library for Keras
TorchGA - Train PyTorch Models using the Genetic Algorithm with PyGAD
tune - An abstraction layer for parameter tuning
evotorch - Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.
mlr3hyperband - Successive Halving and Hyperband in the mlr3 ecosystem
zoofs - zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
baybe - Bayesian Optimization and Design of Experiments
DIgging - Decision Intelligence for digging best parameters in target environment.