ENGR3537 Machine Learning
Machine learning is rapidly reshaping how we live our lives. Machine learning approaches have driven recent progress in an array of technologies that have the potential to realize huge positive impacts on our world (e.g., autonomous driving, language translation, personalized recommendation, large language models, etc). However, the influence of machine learning does not end with these highly visible technologies. Machine learning algorithms are impacting our world in ways that are far less known to the general public, such as in job applicant evaluation, criminal justice, finance, politics, and medicine.
The principal aim of this course is to equip students with a multi-faceted and interdisciplinary skill set to understand, implement, and critically evaluate machine learning systems. In service of this goal, students will learn the major algorithmic and mathematical frameworks that undergird modern machine learning methods. Students will learn effective processes for implementing, testing, and refining machine learning systems across a range of application domains. Students will learn how the decisions that machine learning practitioners make interact with larger societal contexts by considering factors such as transparency, fairness, bias, and privacy.
Concurrent Requisites
MTH2137
Hours
4-0-8