Clustering

Advanced Topics

Clustering

Clustering is method for creating or finding groups. Imagine you’re at a party with your friends, you will naturally start forming smaller groups based on shared interests. For instance, those who enjoy sports might gather together, while those interested in music might gather in another. This process of grouping based on commonalities makes socializing and interacting much easier and more enjoyable.

Clustering is a bit like this above example, but it happens within datasets.  Just as friends who like the same activities naturally stick together toward each other, clustering algorithms group data points together based on certain features they share.

This is tremendously useful because it allows us to uncover patterns and relationships that might not be immediately obvious.

 Clustering in the real world

  • Social Media
    In social media, clustering is like grouping similar puzzle pieces together. It helps platforms like Instagram or Facebook suggest friends who have similar hobbies and arranges posts about food, fashion, or other topics in separate sections. This way, you can easily find what you’re interested in and connect with people who share your passions.
  • Healthcare
    Clustering patient data assists in identifying distinct medical conditions or treatment responses, aiding doctors in providing personalized care based on shared characteristics.
  • Streaming Services
    Platforms like Netflix or PrimeVideos use some sort of clustering techniques to find recommendations for your based on your viewing data. The group the users that share similar viewing history and draw recommendations based on that.

Clustering is big area of study with several techniques and applications. Its impact in the real world is immense and every student of Data Science must explore this topic. 

Activity

 Pokemon Training

In this activity we will do a simple activity to illustrate clustering