In this review, we discuss the data-driven systems and their effects on the implementation of
the inventory theory. After overviewing the theory briefly, we group the data-driven …

In the rapidly evolving landscape of manufacturing, the ability to make accurate predictions
is crucial for optimizing processes. This study introduces a novel framework that combines …

Managers are increasingly being tasked with overseeing data-driven projects that
incorporate prescriptive and predictive models. Furthermore, basic knowledge of the data …

Contribution: This article presents evidence that electrical engineering, computer science,
and data science students, participating in introduction to machine learning (ML) courses …

The newsvendor model is widely used to teach decision making under uncertainty.
Traditionally, analytical methods have been taught to determine the optimal order quantity …

In this paper, we describe a course project in which teams of undergraduate students
propose and execute an end-to-end analytics project to solve a real-world problem. The …

We present an interactive spreadsheet that supports teaching essential concepts in
classification using the logistic regression (LoR) model for binary classification. The …

Анотація На сучасному етапі розвитку інформаційних технологій машинне навчання
(Mashine Learning, ML) та штучний інтелект (Artificial Intelligence, AI) стають одними із …

Motivated by the problem of lineup optimization in wheelchair rugby (WCR), this case study
covers descriptive, predictive, and prescriptive analytics. The case is presented from the …

Machine learning (ML) algorithms are gaining increased importance in many academic and
industrial applications, and such algorithms are, accordingly, becoming common …