Clustering is a machine learning technique that is used to group unlabeled data points so that the data points present in a group are based on similar functionality. If you are looking for some data science case studies on clustering, this article is for you. In this article, I’m going to introduce you to some of the best data science case studies on clustering.
Data Science Case Studies on Clustering
Ted Talks Recommendation System:
Using clustering algorithms helps to find similarities between data points. A recommendation system is an amazing use case for clustering. You must have heard of movies and books recommendation systems. These examples of recommender systems are very popular in the data science community.
So if you want to try something unique, you can create a Ted Talks recommendation system. You can use any clustering technique here, but be sure to find similarities between Ted Talks based on content rather than user interests. You can find this data science case study on clustering solved and explained using Python from here.
Customer Segmentation:
The task of customer segmentation can help a business focus on marketing strategies to increase profits and overall customer satisfaction. It means dividing customers based on certain similarities to find the most profitable target customers.
Thus, in most customer segmentation tasks, a Data Scientist aims to find the category of the most profitable customers from different types of groups. These groups can be formed based on age, income, interests, spending habits, locations, and many other factors depending on the type of product or service your business deals in. You can find this data science case study on clustering solved and explained using Python from here.
Contact Tracing:
Contact tracing helps a lot in tracking the spread of covid-19. When a person is infected with covid-19, it is very important to track their activities to find their contacts with other people. There are many techniques that we can use for contact tracing. But one of the best methods to use for this task is clustering algorithms.
We can use a clustering algorithm on the GPS data to create a digital contact tracing system. You can find this data science case study on clustering solved and explained using Python from here.
Also, Read – Data Science Case Studies on Regression.
Summary
So these were some of the best data science case studies on clustering that you should try. Clustering is a machine learning technique that is used to group unlabeled data points so that the data points present in a group are based on similar functionality. I hope you liked this article on Data Science Case Studies on Clustering solved and explained using Python. Feel free to ask your valuable questions in the comments section below.
