ποΈ Week 07 - Introduction to unsupervised learning and dimensionality reduction
Theme: Unsupervised Learning
Welcome to the seventh week of this course!
This week, we start our exploration of unsupervised learning:
- we discover what differentiates it from supervised learning and in which cases it is used
- we learn about the first family of unsupervised learning techniques: dimensionality reduction. Weβll explain what dimensionality reduction is about and what it is used for before introducing the most common and arguably the most well-known dimensionality reduction algorithm by far: PCA (Principal Component Analysis). We also have a look at a non-linear dimensionality reduction algorithm: UMAP.
π©π»βπ« Lecture Material
π₯ Looking for lecture recordings? You can only find those on Moodle, typically a day after the lecture. If you canβt find the recordings, please contact π§ .
Download the Quarto markdown file for this lecture :