This repository accompanies Bayesian Optimization by Peng Liu (Apress, 2023).
Download the files as a zip using the green button, or clone the repository to your machine using Git.
Release v1.0 corresponds to the code in the published book, without corrections or updates.
See the file Contributing.md for more information on how you can contribute to this repository.
You have three options to set up an environment.
- Use Python
- Use Anaconda
- Use cloud services
This is the simplest of all the options but needs Internet connectivity to use. Cloud providers such as Microsoft Azure Notebooks and Google Collaboratory are popular and available at the following links:
- Microsoft Azure Notebooks: https://notebooks.azure.com/
- Google Collaboratory: https://colab.research.google.com
Anaconda is a Python distribution and made for large data processing, predictive analytics, and scientific computing requirements. The Anaconda distribution is the easiest way to perform Python coding, and it works on Linux, Windows, and macOS.