Machine learning in chemical engineering: Hands-on activities

Abstract

A set of hands-on activities, that were proposed in an introduction course to machine learning in a Chemical Engineering undergraduate course, are presented. The activities aimed to introduce basic concepts of unsupervised learning (e.g., clustering) and supervised learning (e.g., classification and regression). Google Colaboratory, a cloud service provided by Google for free to promote research in Artificial Intelligence and Machine Learning, was used to develop these activities, but the proposed activities can be run similarly in a local Python environment. The datasets used in the activities are publicly available on websites such as Kaggle and University of California (UCI), and a specific example in chemical engineering for the ore grinding process was also used. The student's response to the ML topic within the course was very positive.