Clustering Introduction

We will look at the fundamental concept of clustering, different types of clustering methods and the weaknesses. Clustering is an unsupervised learning technique that consists of grouping data points and creating partitions based on similarity. The ultimate goal is to find groups of similar objects.


– What is clustering?
– Types of clustering methods:
1. Centroid-based clustering
2. Connectivity-based clustering
3. Distribution-based clustering
4. Density-based clustering
– Clustering weaknesses

Previous video:
Introduction to Precision, Recall and F1

Next video:
Natural Language Processing 101

More Data Science Material:
[Video] Introduction to Data Mining
[Video] Introduction to Web Scraping
[Blog] What Machine Learning Tools Should I Learn?


Arham Akheel
About The Author
- Arham holds a Masters degree in Technology Management from Texas A&M University and has a background of managing information systems.


You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>