Prediction Using Unsupervised ML

INTRODUCTION

From the given dataset, predict the optimum number of clusters and represent it visually.
Use R or Python or perform this task

🚀 FEATURES

🔵 Imports the dataset from the given URL
🔵 Loads the dataframe
🔵 Finds the optimum number of clusters for k-means classification
🔵 Plots the results onto a line graph
🔵 Observes the graph
🔵 Creats the kmeans classifier
🔵 Visualises the clusters

📄 REQUIRED DATASET

You can find the required Dataset used in the project here.

🔨 IMPORTING THE LIBRARIES

⚙️ OUTPUT

🖱 FINDING CLUSTERS FOR KMEANS CLASSIFICATION

💎 OUTPUT

⭕️ APPLY KMEANS TO DATASET

📊 VISUALISING THE CLUSTERS

📈 FINAL OUTPUT

🎨 END OF THE PROGRAM

In the end, you can visualise the clusters on the first two columns!

🐛 Bug Reporting

Feel free to open an issue on GitHub if you find any bug.

⭐ Feature Request

Feel free to Create an issue on GitHub to request any additional features you might need for your use case.