📊 K-Means Clustering on Synthetic Data

This project demonstrates the K-Means Clustering algorithm using Scikit-learn. It generates synthetic data with multiple clusters and applies K-Means to identify and visualize them.

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🔍 About the Dataset

The dataset is generated using make_blobs() and contains 300 samples grouped into 4 clusters with 2 features each. This synthetic data is ideal for visualizing unsupervised learning.

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🧠 ML Algorithm: K-Means

This project: Creates clustered data with make_blobs

Applies K-Means clustering with:

k-means++ initialization

4 clusters

300 iterations max

Visualizes the clustered data and centroids using Matplotlib

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⚙️ Tech Stack

Python

NumPy

Matplotlib

Scikit-learn

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📸 Output

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👨‍💻 Author

Syed Imthiaz I
B.E. Computer Science and Engineering
KCG College of Technology
🔗 LinkedIn
🔗 LinkedIn Post

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🚫 License & Disclaimer

© 2025 Syed Imthiaz I — All rights reserved. Unauthorized copying, modification, distribution, or use of this code or any part of it is strictly prohibited without the express written permission of the author.

📩 For permission requests, contact: syedimthiaz2006@gmail.com

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