Treffer: A Gentle Introduction to Machine Learning for Chemists: An Undergraduate Workshop Using Python Notebooks for Visualization, Data Processing, Analysis, and Modeling

Title:
A Gentle Introduction to Machine Learning for Chemists: An Undergraduate Workshop Using Python Notebooks for Visualization, Data Processing, Analysis, and Modeling
Language:
English
Authors:
Lafuente, Deborah (ORCID 0000-0003-3660-7894), Cohen, Brenda (ORCID 0000-0002-6550-9014), Fiorini, Guillermo (ORCID 0000-0003-0992-9812), Garci´a, Agusti´n Alejo (ORCID 0000-0002-6536-4935), Bringas, Mauro (ORCID 0000-0002-2040-3689), Morzan, Ezequiel, Onna, Diego (ORCID 0000-0002-3158-1915)
Source:
Journal of Chemical Education. Sep 2021 98(9):2892-2898.
Availability:
Division of Chemical Education, Inc. and ACS Publications Division of the American Chemical Society. 1155 Sixteenth Street NW, Washington, DC 20036. Tel: 800-227-5558; Tel: 202-872-4600; e-mail: eic@jce.acs.org; Web site: http://pubs.acs.org/jchemeduc
Peer Reviewed:
Y
Page Count:
7
Publication Date:
2021
Document Type:
Fachzeitschrift Journal Articles<br />Reports - Descriptive
Education Level:
Higher Education
Postsecondary Education
Descriptors:
Undergraduate Students, Chemistry, Electronic Learning, Artificial Intelligence, Workshops, Programming Languages, Programming, Visualization, Classification, Regression (Statistics)
DOI:
10.1021/acs.jchemed.1c00142
ISSN:
0021-9584
Entry Date:
2021
Accession Number:
EJ1308965
Database:
ERIC

Weitere Informationen

Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks and assignments. Python, one of the most popular programming languages, is open source, free to use, and has plenty of learning resources. The workshop is designed for students without previous experience in programming, and it aims for a deeper understanding of the complexity of concepts in programming and machine learning. The examples used correspond to real data from physicochemical characterizations of wine, a content that is of interest for students. The contents of the workshop are introduction to Python, basic statistics, data visualization, and dimension reduction, classification, and regression.

As Provided