🎓 Student Clustering System Using Python + ML || Data Science Projects
🎓 Student Clustering System using Python + Machine Learning | CGPA-Based Clustering Web App
Looking to analyze student performance and group them automatically based on CGPA or other academic scores? This Student Clustering System uses KMeans Clustering and provides an interactive web interface using Streamlit to cluster student data and visualize it meaningfully.
📌 Project Summary
This web-based machine learning app allows users to:
Upload student academic data (CSV format)
Automatically apply KMeans clustering
View clustered data in tabular and graphical form
Download the updated dataset with cluster labels
Perfect for educators, analysts, or students exploring unsupervised learning and data visualization in Python!
🔧 Technologies Used
Python
Streamlit (Web UI)
Pandas (Data Manipulation)
scikit-learn (KMeans Clustering, Scaling)
Seaborn / Matplotlib (Charts & Plots)
🔄 How It Works
Upload CSV File: Upload student data with CGPA or numeric scores.
Configure Clustering: Choose the number of clusters using a slider.
KMeans Clustering: Automatically scales data and applies clustering.
Clustered Output: View labeled data in a table and download it.
Visualizations:
✅ Bar Chart – Cluster sizes
✅ Scatter Plot – Visualizes student groups
✅ Pie Chart – Distribution of a selected feature across clusters
✅ Line Chart – Comparison between selected numeric metrics
🎯 Key Features
Upload any student dataset with numeric fields
Auto-selects numeric columns
Configurable cluster count
4 types of visualizations for analysis
Download clustered data as CSV
Suitable for any educational dataset, not just CGPA!
📌 Source Code & Resources:
👉 [Download Source Code](https://updategadh.com/)
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