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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

Screenshot 2021-07-04 at 10 58 47 PM

⚙️ OUTPUT

Screenshot 2021-07-04 at 10 59 42 PM

🖱 FINDING CLUSTERS FOR KMEANS CLASSIFICATION

Screenshot 2021-07-04 at 11 01 36 PM

💎 OUTPUT

Screenshot 2021-07-04 at 11 02 16 PM

⭕️ APPLY KMEANS TO DATASET

Screenshot 2021-07-04 at 11 02 45 PM

📊 VISUALISING THE CLUSTERS

Screenshot 2021-07-04 at 11 05 07 PM

📈 FINAL OUTPUT

Screenshot 2021-07-04 at 11 05 47 PM

🎨 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.