wwu-tinker is an API webservice for hyperparamenter optimization. This free machine learning web service in Python with extensible APIs that researcher can use to tune hyperparameter configuraions.
A simple analogy on hyperparameter tuning. Imagine a recording studio with a sound booth that has devices with dozens of knobs.
The musicians create the music (the parameters), the sound technician adjusts the knobs on the soundboard (the hyperparameters), the output is the quality of music (the cost function).
wwu-tinker is your sound technician of your machine learning projects who adjusts the soundboard to produce quality music.
Python installer:
pip install wwu_tinker
Check out the wwu-tinker wiki for detailed instructions on using our API.
- Setup an Experiment
- Add variables to an experiment
- Submitting an experiment
- Requesting experiment evaluations from server
- Additional experiment tools
In-depth walkthrough.
Iris example
pypi: wwu-tinker
The source code for the API client application is hosted on GitHub.
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