Document Type
Presentation
Publication Date
4-1-2026
Keywords
Machine Learning, Structured Data, Supervised Learning, Data Science, AI Workshop, PEAAII, UMass Boston
Disciplines
Computer Sciences | Education | Engineering
Abstract
This workshop introduces the fundamentals of machine learning for structured data, focusing on tabular datasets and real-world applications. Participants explore key concepts such as data types, data preprocessing, feature engineering, and supervised learning methods. The session covers commonly used models, including linear regression, logistic regression, decision trees, and neural networks, along with evaluation metrics such as RMSE, accuracy, and confusion matrices. By the end of the workshop, participants will have gained a practical understanding of how to build, interpret, and evaluate machine learning models for structured data.
Recommended Citation
Saha, Moumita, "AIW26S: Machine Learning of Structured Data" (2026). Paul English Applied Artificial Intelligence (AI) Institute Publications. 26.
https://scholarworks.umb.edu/ai_pubs/26
Rights
© 2026 Moumita Saha
Comments
Free and open access to this work is made available to the UMass Boston community by ScholarWorks at UMass Boston. Those not on campus and those without a UMass Boston campus username and password may gain access to this work through Interlibrary Loan. If you have a UMass Boston campus username and password and would like to download this work from off-campus, click on the “Off-Campus Users” button.