Lecture III - Unsupervised Learning
The goal for this lecture is to familiarize the students with some of the basic unsupervised and dimensionality reduction algorithms and their applications. In particular:
Sept 6, 2017 - 12:15-13:10
- Types of Machine Learning
- Data Normalization
- Clustering
- K-Means
- Silhouette Analysis
- Expectation Maximization
- Gaussian Mixture Models
- Principal Component Analysis
By the end of the lecture the students will understand clustering and dimensionality reduction analyses.