Machine Learning Foundations and Practice
This course covers fundamental concepts, methods, and tools for machine learning using Python. We will emphasize a learn by doing approach with a heavy reliance upon exercises and assignments in Python and utilizing modern ML packages. Jupyter notebooks will be used as a framework for combining machine learning models with notes documenting the design and development of experiments. You will learn the basics of data representation and visualization, as well as common, well-established practices for characterizing and classifying data. You will also learn to develop and apply modern machine learning models and, most importantly, understand the process that underlies the design and conduct of effective machine learning experiments.
Important Note about Communication: Unless it is a sensitive matter, all emails regarding the class should be forwarded to the email id compsci_cs345@colostate.edu. This will be actively monitored by the TAs and the instructor. We will also have a teams channel for the class that will be monitored.
2026 Spring Semester Details
Instructor(s)
|
Instructor |
Sarath Sreedharan |
|
Office |
CSB 466 |
|
|
|
|
Office Hours |
TR 12:30 – 1:30 (in-person and online via teams. |
Class Schedule
|
Section |
Schedule |
Location |
Instructor |
|---|---|---|---|
|
001 |
TR 11:00a – 12:15p |
TILT 221 |
Sreedharan |
|
801 |
Async |
Online |
Sreedharan |
TA Office Hours
| Septia Rani | Tuesday 4 PM-5 PM (CSB 120) Tuesday 8 PM-9 PM (CSB 120) Thursday 4 PM-5 PM (CSB 120) Sunday 7 PM-8 PM (Online) |
| Trisha Ghali | Tuesday 4 PM-5 PM (CSB 120) Tuesday 8 PM-9 PM (CSB 120) Thursday 4 PM-5 PM (CSB 120) Sunday 7 PM-8 PM (Online) |
| Artemio | Tuesday 4 PM-5 PM (CSB 120) Tuesday 8 PM-9 PM (CSB 120) Thursday 4 PM-5 PM (CSB 120) Sunday 7 PM-8 PM (Online) |
| Coen | Tuesday, Thursday:9:30AM- 11:30AM( CSB 120) Friday: 11:00 AM – 1:00 PM ( CSB 120) |
| Ziqui | Monday 9 AM-11 PM (CSB 120) Wednesdays 2 PM-4 PM (CSB 120) |