Student Performance Analysis & Prediction using Machine Learning

Python Notebook

₹999.00₹899.00

Complete Data Science Project with Regression, Classification, SMOTE and Model Evaluation using Python.

Student performance prediction is an important application of data science in education analytics.

This project analyzes student academic data and predicts final performance using Machine Learning algorithms in Python.

The project demonstrates a complete ML workflow including data preprocessing, feature scaling, regression modeling, classification, and evaluation.

It is perfect for:

The notebook is well commented and beginner friendly, making it easy to understand the entire machine learning pipeline.

Key features

✔ Data understanding and exploration

✔ Data preprocessing and feature scaling

✔ Regression modeling for score prediction

✔ Classification of student performance

✔ Handling imbalanced datasets using SMOTE

✔ Model evaluation using ML metrics

✔ Educational data analytics techniques

Machine Learning Techniques Used

Technologies Used

Project Workflow

1️⃣ Data Loading and Understanding

2️⃣ Exploratory Data Analysis

3️⃣ Feature Selection

4️⃣ Data Normalization (MinMaxScaler)

5️⃣ Train-Test Split

6️⃣ Regression Model Training

7️⃣ Classification Model Training

8️⃣ Handling Class Imbalance using SMOTE

9️⃣ Model Evaluation and Metrics

🔟 Result Interpretation

Files Included

✔ Student Performance Prediction.ipynb

✔ Dataset (student_performance.csv)

✔ Well-commented Python code

✔ Machine learning models and evaluation

✔ Documentation

✔ Powerpoint Presentation

Perfect for::

* Students learning Machine Learning with Python

* College students needing final year project reference

* Beginners building Data Science portfolio

* Teachers looking for ML practical examples

You will get the following files: