Project
Student: Ayesha Anjum (h98765432hammad@gmail.com)
ML Student Performance Prediction
Updated: 2026-03-18 17:28:25
Not Started
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Student details
Ayesha Anjum
Roll no: BSSCI-22-31
Batch: 2022-2026
Program: BSIT
Phone: 0370 4210085
Supervisor assigned
Amna Tariq
Email: amnatariq@bsit.gcsmultan.edu.pk
Phone: 03166338448
Department: CS
Description
This project aims to develop a Machine Learning-based system to predict student performance. The system will use data such as attendance, marks, and study hours to analyze student progress. Machine learning algorithms like Decision Tree or Linear Regression will be used to make predictions.
The system will help teachers identify weak students and take early actions to improve their performance. A simple interface will also be developed for easy use..
This project aims to develop a Machine Learning-based system to predict student performance. The system will use data such as attendance, marks, and study hours to analyze student progress. Machine learning algorithms like Decision Tree or Linear Regression will be used to make predictions.
The system will help teachers identify weak students and take early actions to improve their performance. A simple interface will also be developed for easy use..
Technologies
Python
CSV Dataset / Kaggle Dataset / SQLite
Streamlit / Flask
Python Libraries: Scikit-learn, Pandas, NumPy, Matplotlib
Jupyter Notebook
VS Code / PyCharm
Python
CSV Dataset / Kaggle Dataset / SQLite
Streamlit / Flask
Python Libraries: Scikit-learn, Pandas, NumPy, Matplotlib
Jupyter Notebook
VS Code / PyCharm
| Uploaded | File | Size | SHA256 | Open |
|---|---|---|---|---|
| 2026-03-18 16:43:32 | BSSCI-22-31 .pdf | 63.8 KB | 750ba788d37b7b6366d8aa1b9072046524ecdf2222e81fe9559318dbe20f8e9f | Open |