hyperas
Hyperparameter optimizer
A simple wrapper around Keras and Hyperopt for convenient hyperparameter optimization.
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
2k stars
63 watching
318 forks
Language: Python
last commit: almost 2 years ago
Linked from 5 awesome lists
hyperopthyperparameter-optimizationkeras
academic/awesome-datascience
kelvins/awesome-mlops
krzjoa/awesome-python-data-science
ahundt/awesome-robotics
markusschanta/awesome-kerasRelated projects:
| Repository | Description | Stars |
|---|---|---|
 hyperopt/hyperopt-sklearn | Automates search for optimal parameters in machine learning algorithms. | 1,588 |
 huntermcgushion/hyperparameter_hunter | Automates hyperparameter optimization and result saving across machine learning algorithms | 706 |
 guillaume-chevalier/hyperopt-keras-cnn-cifar-100 | Automates hyperparameter optimization and neural network architecture search using Hyperopt on a CNN model for the CIFAR-100 dataset | 106 |
 automl/smac3 | An optimization framework for machine learning hyperparameters | 1,085 |
 claesenm/optunity | A collection of algorithms for hyperparameter optimization in machine learning models | 416 |
 gdikov/hypertunity | A toolset for optimizing hyperparameters of machine learning models using Bayesian optimization and real-time visualization. | 136 |
 syne-tune/syne-tune | A tool for large-scale and asynchronous hyperparameter optimization in machine learning | 390 |
 rodrigo-arenas/sklearn-genetic-opt | Automated hyperparameter tuning and feature selection using evolutionary algorithms. | 314 |
 instrat-pl/pypsa-pl | An optimisation model of the Polish energy system using PyPSA framework | 21 |
 lucfra/far-ho | A package for optimizing hyperparameters and meta-learning using gradient-based methods in TensorFlow. | 187 |
 kirthevasank/nasbot | An implementation of neural architecture search with Bayesian optimization and optimal transport | 133 |
 lge-arc-advancedai/auptimizer | Automates model building and deployment process by optimizing hyperparameters and compressing models for edge computing. | 200 |
 guopengf/auto-fedrl | A reinforcement learning-based framework for optimizing hyperparameters in distributed machine learning environments. | 15 |
 autonomio/talos | A tool for automating hyperparameter experiments for machine learning models using TensorFlow and Keras | 1,625 |
 herilalaina/mosaic_ml | Automated machine learning with tree search optimization | 16 |