K-Means Clustering of Iris Dataset

This is Task-2 of The Sparks Foundation GRIP. This task is based on Unsupervised Machine Learning.

In this repository I used K-Means Clustering to make clusters of Iris data on their features.

For more information about K-Means Clustering you can refe this (https://towardsdatascience.com/k-means-clustering-algorithm-applications-evaluation-methods-and-drawbacks-aa03e644b48a).

Code of K-Means Clustering of Iris Dataset

To understand this repository follow the below steps:

1. First Clone, Fork or Download this repository or you can run Task2Colab.ipynb on Google Colab.

2. The dataset used is (https://bit.ly/3kXTdox).

3. Now, you can run Task2.ipynb or Task2Colab.ipynb file locally or online.

4. I used inbuild Scikit Learn libraries of K-Means clustering.

5. All, the uses and instructions are written in code file itself.

Note - For any suggestion or recommendations you can send me pull request.