Bayesian optimisation

How to find the best parameters of any algorithm.

Notebooks

Follow along with these notebooks:

You will need the following python libraries: scikit-learn, jupyter, matplotlib, scikit-optimize* and their dependencies.

To install scikit-optimize use:

$ pip install https://github.com/scikit-optimize/scikit-optimize/archive/1677188ee6de3365f7925de780dd2f31e5e34ee4.zip

This will install a particular snapshot of the library that is known to work. You can probably use pip install scikit-learn as well.

Name		Name	Last commit message	Last commit date
Latest commit History 11 Commits
.gitignore		.gitignore
01-scipy-optimize.ipynb		01-scipy-optimize.ipynb
02-bayesian-optimisation.ipynb		02-bayesian-optimisation.ipynb
03-acquisition-functions.ipynb		03-acquisition-functions.ipynb
04-regression-with-errorbars.ipynb		04-regression-with-errorbars.ipynb
05-bayesian-beer.ipynb		05-bayesian-beer.ipynb
README.md		README.md
beer-tasters.ipynb		beer-tasters.ipynb
lissajous.ipynb		lissajous.ipynb
plots.ipynb		plots.ipynb
requirements.txt		requirements.txt
utils.py		utils.py