Intermediate Data Analytics and Machine Learning
CMDA/CS/STAT 4654 is a technical analytics course that will teach supervised and unsupervised learning strategies,
including regression, generalized linear models, regularization, dimension reduction methods, tree-based methods for
classification, and clustering. Upper-level analytical methods are shown in practice: e.g.,
neural networks and Gaussian processes. It is targeted towards students who have completed (and remember the concepts
from) a course in introductory statistics and mathematical modeling.
We will make extensive use of calculus, linear algrbra, and probability.
Computational tools, such as the
R language for statistical
computing, will be used for illustration in class be essential for completing homework problems.
- Class is canceled on Wednesday Feb 7. Office hours on Tuesday Feb 6 are canceled. Monday and Wednesday (TA) office hours are still on. Homework 1 is still due Feb 7.
- The TA will hold office hours in the Old Security Building, Wed 1-2pm and Thu 11am-12pm.
- Lectures will primarily be slides-based, supplemented by board calculations and computing demonstration in
R. For complete notes you must come to class!
Homework Due at the start of lecture
The recommended language for this course is
which can be obtained from CRAN.
Other languages such as
MATLAB are allowed but are not recommended.
Examples in lecture, and help in office hours, etc., will be exclusively in
Below are some helpful