Portfolio Details
Have a look at my Portfolio...
Student Performance Classifier Model
A machine learning model to classify student performance based on academic data.
Project Overview
This project focuses on classifying student performance using machine learning techniques. The goal is to predict student outcomes based on various factors such as attendance, grades, and demographic data. The model was built using Python and Streamlit for visualization.
The Challenge
Classifying student performance accurately is a complex task due to the variety of factors involved. The challenge was to build a model that could effectively predict student outcomes based on multiple input features.
Our Approach
We used a combination of data preprocessing, feature engineering, and machine learning algorithms to build a robust classification model. The dataset was cleaned and normalized, and we employed techniques like cross-validation to ensure the model's reliability and generalizability.
Technology Stack
Key Features
This project includes key features such as data preprocessing, model training, and visualization using Streamlit.