Module: Cluster Analysis

How do we find natural groupings in the data?

Learning Outcomes

Understand how to perform cluster analysis

You understand

what problems are addressed by cluster analysis
how to analyze data using clustering techniques
what are the limitations of clustering techniques
how the k-means technique works
how the agglomerative hierarchical clustering technique works
how density-based clustering works
how topic modeling works
how recommender system works
how to apply clustering to real world scenarios

Readings

Latent Dirichlet Allocation

Slides

Frequent Itemsets

Slides

Finding the Number of Clusters

wikipedia

Quick Guide to Build a Recommendation Engine in Python

Recommender Systems & Collaborative Filtering

Python Package: Implicit

Fast Python Collaborative Filtering for Implicit Datasets.

Python Package: Spotlight

Python Collaborative Filtering.

Perplexity Intuition

Measure of goodness for topic models

Experiential Learning

k-means

k-means clustering

LDA

Topic Modeling