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

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

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).

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

Dead Simple Result Analysis for VTU Engineering Students

This repository is made by RENZ DEXTER M. PERCI for the subject CSST 104, ADVANCE MACHINE LEARNING

Statistical data analysis report on Kaggle dataset Student Performance made as a personal project.

Project for VTU result analysis, extraction and visualisations.

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.

A machine learning project aimed at predicting student performance using various ML algorithms. Features data preprocessing, model training, and evaluation. Ideal for educational data analysis and academic research.

Regression Analysis using dataset from different Industries

This repository contains a comprehensive analysis of student progress using various factors like extracurricular activities, parental support, gender, ethnicity, and more. The dataset includes 2,392 students and examines how different variables influence academic performance and participation in extracurricular activities.

Developed an end-to-end machine learning project using Docker and AWS, and implemented an industrial-grade code with modular architecture. The project focused on student performance prediction, achieving high accuracy through various machine learning algorithms.

This project predicts students' math scores using machine learning and Flask for real-time predictions.

This project delves into the key factors impacting student performance, from demographics to study habits. Leveraging Python for in-depth analysis and visualizations, it reveals actionable insights to enhance academic success and optimize learning outcomes.

Öğrencilerin sınavda gösterdiği performansa göre analiz

SQL script to answer the past "365 Learning Data Challenge"

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.

An advanced machine learning project for analyzing student performance, utilizing sociodemographic indicators. Hosted on AWS Elastic Beanstalk for real-time predictions and integrated with AWS CodePipeline for continuous integration and deployment.