student-performance-analysis

This project analyses and correlates student performance with different attributes. Then at last, it determines most suitable algorithm from bunch of them.

The Exploratory Data Analysis and Machine Learning Model Training for the Student Performance Data

AI-powered EduPredict: A student performance and analytics system using Machine Learning and Streamlit. Predicts outcomes, identifies risk factors, and provides actionable insights for educators.

Utilizes Pandas, Matplotlib, and NumPy to analyze grades, subjects, and study habits. Gain insights into academic performance through data analysis and visualization.

This is our Mini Project for 6th semester. In this Mini Project we are developing a new webapp in which we will be performing data visualisation, dashboard designing web development using HTML5,CSS, JavaScript for web development. We are also using tools like Power BI or Tabelue for visualisation purpose.

This dashboard represents an analysis on student performance in math, reading, and writing examinations where more than one factor has been taken into consideration. in accordance with #InternIntelligence.

Predicting student academic performance using a machine learning approach. This project leverages the Random Forest Classifier algorithm.

Data analysis project using Python (Pandas, Matplotlib) to analyze student performance and generate insights.

To understand and predict how the student's performance (test scores) is affected by the other variables (Gender, Ethnicity, Parental level of education, Lunch, Test preparation course).

The primary objective of this project is to develop a predictive model that can forecast the performance of students in their academic projects. The model aims to help educators and institutions identify students who may need additional support or intervention early in the project development process, ultimately enhancing overall student success.

Dead Simple Result Analysis for VTU Engineering Students

This project performs Exploratory Data Analysis (EDA) and hypothesis testing on student performance data. It explores trends based on attributes like gender, race/ethnicity, parental education, lunch type, and test preparation course completion.

The dataset is designed for predicting whether a student will pass or fail an exam based on the number of study hours and their scores in the previous exam.

Analyzes student behavior patterns to understand their impact on academic performance. Provides clear visual insights and correlations from real data. Supports early prediction and decision-making for improving student outcomes.

Student performance dashboard using Python & Streamlit

Exploratory Data Analysis (EDA) of student performance using Python to uncover factors affecting academic scores through statistical analysis and data visualization.

Taking part in Kaggle challenges or simply picking random datasets and working on them

Django-based Student Performance Analysis System with Admin, Staff, and Student portals, featuring marks management, CGPA calculation, leaderboards, and interactive performance analytics dashboards.

A Flask web application that processes student test data and generates AI-powered personalized PDF reports with performance analytics, visualizations, and actionable recommendations using Google Gemini API.