HunterMcGushion/hyperparameter_hunter
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
This tool helps machine learning practitioners efficiently manage and optimize their model experiments. You provide your dataset and define your model's hyperparameters using familiar libraries like Keras or Scikit-learn, and the tool automatically tracks results, scores, and configurations. It's designed for data scientists, machine learning engineers, and researchers who regularly train models and need to systematically improve their performance.
708 stars. Used by 1 other package. No commits in the last 6 months. Available on PyPI.
Use this if you regularly run machine learning experiments and want to automate the tracking and informed optimization of model hyperparameters across various algorithms and libraries.
Not ideal if you only occasionally train a single model and don't require systematic experimentation or hyperparameter tuning.
Stars
708
Forks
101
Language
Python
License
MIT
Category
Last pushed
Jan 20, 2021
Commits (30d)
0
Dependencies
10
Reverse dependents
1
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