Machine learning in chemical engineering: Hands-on activities

被引:4
|
作者
Lavor, Vitor [1 ,2 ]
de Come, Fernando [1 ]
dos Santos, Moises Teles [1 ]
Vianna, Ardson S. [1 ]
机构
[1] Univ Sao Paulo, Dept Chem Engn, Ave Prof Luciano Gualberto 380, BR-05508010 Sao Paulo, Brazil
[2] Univ Reading, Sch Built Environm, Reading, England
关键词
Machine Learning; Hands-on; Clustering; Classification; Regression; ANN;
D O I
10.1016/j.ece.2023.09.005
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
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.
引用
收藏
页码:10 / 21
页数:12
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