C) Intro to Unsupervised Machine Learning (W38)

Note: Note: Unsupervised Machine Learning Assignment Submission Deadline: Friday, 20 September 2024, 12:00

This topic includes 5 sessions as follows:

• Introduction to Unsupervised Machine Learning (Mon, Sep 16th, 12:30-16:15): This session will dive into the foundational concepts and real-world uses of unsupervised machine learning (UML). As part of this, students will gain insights into various UML challenges. Furthermore, they will explore notable UML algorithms, including PCA, SVD, NMF, and an introduction to clustering via k-means.

• UML 2: Geospatial Data (Tue, Sep 17th, 08:15-12:00): This session will focus on geospatial data and its application to UML. Students will learn about different methods to analyze and visualize spatial data using UML techniques.

• UML 3: Recommendation & Similarity Search (Fri, Sep 20th, 08:15-12:00): This session will explore the application of UML to recommendation systems and similarity search. Students will learn about different types of recommendation systems and explore how UML can improve recommendation accuracy and relevance.

• Clustering Techniques: K-means & Hierarchical (Fri, Sep 20th, 08:15-12:00): This session will introduce the principles and applications of clustering, including popular algorithms like K-means and hierarchical clustering.