Lokeshrathi / Clustering_algorithm_solution

This repo consists of Projects related Clustering with solutions.

Under this repo, I have curated few business problems that can be solved using KMeans clustering algorithm.

Clustering Project -1

In clustering, the objective is to ensure that the variations within a cluster is minimized, while the variations between the clusters is maximised.

The dataset consists of 2 columns

1. age
2. salary

Task: To analyse and understand the customer segments that might exist and identify the key attributes of each segment.

Result: Data was divided into 3 segments and inferences were made accordingly.

---

Clustering Project - 2

Creating Product Segments using Clustering

The dataset consists of 5 columns:

1. name
2. calories
3. sodium
4. alcohol
5. cost

Business Problem: A company would like to enter the Beer market with a new beer brand. Before, it decides the kind of beer it will launch, it must understand what kind of products are already available in the market and what kind of segments the products address.

Found the Number of clusters via the Elbow curve method:

Elbow Curve method considers the percentage of variation explained as a function of the number of clusters.

Clustering Project -3

Creating Customer Segmentation using Clustering(KMeans)

The dataset consists of 5 columns:

1. Customer_id
2. Gender
3. Age
4. Annual Income
5. Spends

Business Problem: You own the mall and want to understand the customers like who can be easily converge [Target Customers] so that the sense can be given to marketing team and plan the strategy accordingly.