This paper and code will help industrial users, data analysts, and researchers to better develop machine learning models by identifying the proper hyper-parameter configurations effectively.

- PS: A comprehensive **Automated Machine Learning (AutoML)** tutorial code can be found in: [AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics](https://github.com/Western-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics)

* Including **automated data pre-processing, automated feature engineering, automated model selection, hyperparameter optimization, and automated model updating** (concept drift adaptation).

On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice

[One-column version: arXiv](https://arxiv.org/abs/2007.15745)