Office of the Registrar
Campus Address
Hanover, NH
Phone: (603) 646-xxxx
Fax: (603) 646-xxxx
Email: reg@Dartmouth.EDU

New Undergraduate Course Supplement 2022

ENGS 85.10 Mathematical Foundations for Machine Learning

Mathematics for Machine Learning aims to lay the mathematical foundation that are key to understanding the motivations and the implementation ML algorithms. This course will cover the following four broad topics; namely, vector calculus, probability theory, matrix algebra and optimization, in so far as they are used in ML algorithms. The course will conclude with application of these topics to four prototypical ML tasks/algorithms – two in supervised learning (regression using linear models and classification using support vector machine), and two in unsupervised learning (clustering using expectation maximization (EM) and dimensionality reduction using Principal Component Analysis (PCA).  Programming at the level of Python and ML software packages (PyTorch, Tensorflow, etc.) will be used to supplement the understanding of the mathematics and algorithms, though the focus of the course will be on developing mathematical foundations and intuitions for the ML algorithms, rather than on developing large-scale applications of ML algorithms. 

The Timetable of Class Meetings contains the most up-to-date information about a course. It includes not only the meeting time and instructor, but also its official distributive and/or world culture designation. This information supersedes any information you may see elsewhere, to include what may appear in this ORC/Catalog or on a department/program website. Note that course attributes may change term to term therefore those in effect are those (only) during the term in which you enroll in the course.