WEEK 8

Posted 2021-01-24 keyshaw

WEEK 8

Unsupervised Learning

We use unsupervised learning to build models that help us understand our data better. We discuss the k-Means algorithm for clustering that enable us to learn groupings of unlabeled data points.
5 videos, 1 reading

Video: Unsupervised Learning: Introduction

Video: K-Means Algorithm

Video: Optimization Objective

Video: Random Initialization

Video: Choosing the Number of Clusters

Reading: Lecture Slides

Graded: Unsupervised Learning

Dimensionality Reduction

In this module, we introduce Principal Components Analysis, and show how it can be used for data compression to speed up learning algorithms as well as for visualizations of complex datasets.
7 videos, 1 reading

Video: Motivation I: Data Compression

Video: Motivation II: Visualization

Video: Principal Component Analysis Problem Formulation

Video: Principal Component Analysis Algorithm

Video: Reconstruction from Compressed Representation

Video: Choosing the Number of Principal Components

Video: Advice for Applying PCA

Reading: Lecture Slides

Programming: K-Means Clustering and PCA

Graded: Principal Component Analysis