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

BRENDA COHEN; MAURO BRINGAS; GUILLERMO FIORINI; EZEQUIEL MORZAN; DEBORAH LAFUENTE; AGUSTÍN ALEJO GARCÍA; DIEGO ONNA

JOURNAL OF CHEMICAL EDUCATION

AMER CHEMICAL SOC

Lugar: Washington; Año: 2021

0021-9584

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.