Statistical Machine Learning
10:10am–11:25am
HAMILTON HALL HAM 517
Morningside
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
Description
Prerequisites: STAT GU4206. The course will provide an introduction to Machine Learning and its core models and algorithms. The aim of the course is to provide students of statistics with detailed knowledge of how Machine Learning methods work and how statistical models can be brought to bear in computer systems - not only to analyze large data sets, but to let computers perform tasks that traditional methods of computer science are unable to address. Examples range from speech recognition and text analysis through bioinformatics and medical diagnosis. This course provides a first introduction to the statistical methods and mathematical concepts which make such technologies possible
Reviews
Course experience
Aggregated across everyone who has taught this course.
No reviews matched yet.
Instructor quality
Aggregated across every course Genevera Allen has taught.
No reviews matched yet.
In your week
Where it meets
Flat map — motion reduced
Workload and grading
- Grading
- Not published
- Format
- Not published
- Credits
- 3 credits
Reported workload
From CULPA and Reddit reviews matched to this course.
No reviews matched yet.