Student performance prediction github. Extraction of factors impacting students' performances.

Student performance prediction github Built with React, TypeScript, and Tailwind CSS, featuring machine learning algorithms to analyze student data and provide actionable insights Problem Statement - Predicting the Students performance using Machine learning based on their previous data and results for early prevention. 9888. Project Overview This project aims to predict student performance in competitive exams based on key factors such as attendance, study hours, previous grades, extracurricular activities, and parental support. A machine learning algorithm is developed to predict student performance on the test according to the features available in the dataset. Applied Science, 2020" - ypzhaang/student-performance-prediction The primary objective of this project is to develop a predictive model that can forecast the performance of students in their academic projects. By analyzing past performance data and current lifestyle choices, the system This project explores various machine learning techniques to predict student performance in higher education. The analysis covers various factors influencing academic performance and employs a wide range of statistical and data-driven methods. It explores various machine learning algorithms, selects the best-performing model, and deploys it using Flask for user interaction. Features include Decision Tree, Dec 2, 2021 · This problem focuses on predicting a student's performance in school based on a number of characteristics related to the student's lifestyle, personal traits, and current living situation. The data attributes include student grades, demographic, social and school related features) and it was collected by using school reports and questionnaires. By leveraging data analysis and machine learning techniques, this project seeks to provide insights into the factors influencing An interactive student performance monitoring system developed using Django framework, along with a combination of JavaScript, HTML, CSS, and Python. The model aims to help educators and institutions id Student Performance Prediction This project allows you to predict student performance in exams using machine learning techniques. By using machine learning, we aim to help educators identify at-risk students and provide interventions to improve their outcomes. This project aims to predict student performance based on various factors such as study time, past grades, extracurricular activities, and parental education. Upload CSV files, get predictions, and visualize results instantly. Graphs Regularized Robust Matrix Factorization and Its Application on Student Grade Prediction. Welcome to the Student Performance Prediction and Analysis repository—a place where data science meets the drama of student life! Whether you're here to flex your ML skills or just curious about what makes students tick (spoiler: it’s probably coffee), this repo has got you covered. The project aims to support early interventions for students at risk of underperforming academically. The project includes exploratory data analysis, model development with XGBoost, and actionable policy recommendations based on data-driven insights Explore the provided Jupyter Notebook (Student Performance Prediction-Linear Regression. edu/ml/index. This GitHub repository contains code for a student performance prediction model utilizing linear regression. The machine learning model trained on a dataset of student information can provide insights into predicting a student's performance in mathematics. However, this model is a bit different. This data approach student achievement in secondary education of two Portuguese schools. Student Performance Prediction: Python project using machine learning to predict student success based on hours studied, attendance, past scores, and extra classes. A linear regression model trained using gradient descent to predict student grades based on the following characteristics: 1. To study the existing prediction methods for predicting students performance. A machine learning project aimed at predicting student performance using various ML algorithms. To study and identify the gaps in existing prediction methods. Built using Python, pandas, seaborn, and scikit-learn, with Linear Regression as the main algorithm. In this analysis we will focus on the final grade and classify them as pass or fail. Contribute to RohithYogi/Student-Performance-Prediction development by creating an account on GitHub. Contribute to Celein0110/student-performance-prediction development by creating an account on GitHub. The project encompasses data preprocessing, exploratory data analysis (EDA), model selection, training, and deployment. It analyzes quiz, project, and peer review scores to identify key performance indicators. 95. The project is implemented and can be executed in Google Colab This code is for "Yupei Zhang, Yue Yun, Huan Dai, Jiaqi Cui, and Xuequn Shang. Student Performance Analysis and Prediction This repository contains a data science project focused on analyzing and predicting student performance based on various factors. The project aims to develop a system that predicts About The "Students Performance Prediction" project leverages machine learning and Django to predict student outcomes based on factors like attendance, study habits, and past grades. study_daily 3. The Indian Student Performance Prediction project aims to analyze and predict students' academic performance based on various socio-demographic and academic factors. Welcome to the Student Performance Indicator Prediction repository! This project aims to predict student performance indicators based on various features such as gender, ethnicity, parental education, lunch type, and test preparation. This project uses multiple linear regression to analyze student performance based on 10,000 observations. - papeye/ANN-Students-Performance-Prediction This project understands how the student's performance (test scores) is affected by other variables such as Gender, Ethnicity, Parental level of education, Lunch and Test preparation course Predicting academic outcomes helps educational institutions tailor interventions, develop better learning strategies, and assist underperforming students. Explore and run machine learning code with Kaggle Notebooks | Using data from Students' Academic Performance Dataset Sep 13, 2023 · This machine learning project takes different attributes from the data set and predict the student’s final grade/performance by using linear regression algorithm. soc_score [0 - 1] 2. This project implements a machine learning model to predict student exam scores using Linear Regression. Contribute to Vihar20033/ML-Powered-Student-Performance-Prediction development by creating an account on GitHub. This documentation is inspired by a series of videos from Krish Naik YouTube channel. The aim is to identify key factors influencing student outcomes and build a predictive model for final scores. The model is built using relevant student data features and implements one-hot encoding for categorical variables. The model A comprehensive AI-powered web application for predicting student academic performance and identifying at-risk students. The system analyzes various factors including study hours, attendance, parental involvement, and other educational and environmental factors to provide accurate performance predictions. The prediction model can be used by educators to identify students who may require additional support or interventions, enabling a more personalized learning experience. In the CustomData class, gets the feature values inserted by the user in the html page and creates a dataframe with this information. This project focuses on predicting writing scores using a comprehensive dataset compiled from various educational platforms. - GitHub - rashiyadav05/ Student Performance Prediction with Flask Deployment Overview This repository houses an end-to-end machine learning application designed to predict student performance. With the increasing availability of data on student demographics, academic history, and other relevant factors, schools and universities are using advanced analytics and machine A machine learning project aimed at predicting student performance using various ML algorithms. Study and review some articles to get an idea for choosing or selecting online learning behavior indicators and dimensions in online learning for the student performance prediction model. This project provides several techniques which tries to improve K-means clustering, some techniques are like “Salp swarm Optimization”, "Chaotic Salp swarm", “Grey Wolf This project aims to predict student performance based on various factors such as study time, past grades, extracurricular activities, and parental education. The dataset focuses on student performance in two subjects, mathematics and Portuguese. This project aims to predict student performance based on various features such as study time, past grades, and other relevant factors. The study utilizes supervised, semi-supervised, and unsupervised learning algorithms to identify students at risk of academic failure. Jun 27, 2025 · 🎓 Student Performance Prediction This project predicts whether a student will pass or fail based on various features such as gender, parental education, study time, and test scores. Predicting students performance in exams using machine learning classifiers : Logistic regression, KNN and SVM. The Student Performance Prediction project is a web application that predicts the academic performance of students based on various input features. It provides insights into the relationships between academic performance and factors like study habits, parental About Student Performance Analysis & GPA Prediction using EDA and Machine Learning. A Streamlit web application also allows users Student-Performance-Prediction Using Machine learning to predict a student final grade I made this project to practices and experement with some of the dimentsionality reduction techniques like low variance filter, cheking multicollinearity, random forest feature importance and principal component analysis The Student Result Prediction System uses AI to predict whether students will pass or fail based on factors like attendance, assignment scores, and previous academic performance. Then we will use this data set to train various machine learning classification models and try to come up with the best performing classification model. ics. Includes data preprocessing, model training, evaluation, and a simple interface for generating predictions. This dataset is sourced from a study on student behaviors and academic outcomes, aiming to identify patterns that can inform educational strategies. The goal of this project was to predict the future score of students based on their historic performance data. By leveraging machine learning techniques, the project seeks to identify key indicators that influence student grades and provide actionable insights for educators and students. If you are not on the most recent version, your problem may have been solved already! Upgrading is always the best Student-Performance-Prediction-using-Data-Mining-Techniques Introduction Here, I have tried to identify and evaluate the impact of the Covid-19 pandemic and its subsequent fallout in predicting student’s academic performance. Prediction: Based on the input details, the app predicts the student's math score. The primary objective of this project is to develop a predictive model that can forecast the performance of students in their academic projects. For this, a data set of various undergraduate students was compiled from March 2021. Student-Performance-Prediction This project predicts the performance of the student on the basis of the given dataset. The aim is to build a robust and efficient prediction system using various machine learning techniques. The dataset includes information known at the time of student enrollment (academic path, demographics, and social-economic factors) and the students' academic performance at the end of the first and second semesters. Jan 25, 2025 · Contribute to shivaragula/Student-performance-and-difficulties-prediction development by creating an account on GitHub. Prediction using Flask The predic_pipeline. This project aims to predict student performance based on various factors such as gender, ethnicity, parental level of education, lunch type, test preparation course, and exam scores. The dataset used in this project, the "Student Performance Dataset," includes various features related to students' grades, demographics, social factors, and school-related aspects. The Student Performance Analysis System utilizes machine learning algorithms to forecast student performance based on factors such as demographics, previous grades, attendance, and other relevant indicators. It goes beyond basic features by introducing custom-engineered attributes that significantly improve prediction accuracy. This is a machine learning algorithm for predicting student performance using the Linear Regression technique. Apr 18, 2025 · A machine learning project that analyzes student performance data and predicts final exam outcomes based on internal exam scores and attendance records. The project includes data Problematic As already mentioned, with the help of the old students records, we can came up with a model that can let us help students improve their performance in exams by predicting the student success. A Linear Regression model achieved an R² score of 0. The data attributes include student grades, demographic, social and school related features and it was collected by using school reports and questionnaires. Using a dataset from Kaggle, the project utilizes a modular approach with distinct components for data ingestion, transformation, and model training. Machine learning . Two datasets are provided regarding the performance in two distinct subjects: Mathematics (mat) and Portuguese language (por). Ideal for educational data analysis and Student Performance Prediction This repository contains a project aimed at predicting student performance using machine learning models. About ANN-LSTM model to predict student performance on OULAD dataset jupyter notebook Contribute to ankitanand17/Student_performance_prediction development by creating an account on GitHub. The Student Performance Prediction System uses machine learning to predict academic outcomes based on student data. A comprehensive machine learning project that predicts student mathematics performance using demographic, socioeconomic, and behavioral factors. Student performance prediction using machine learning ensemble techniques Introduction The objective of the project was to write a program which would be able to predict student performance based on various qualitative and quantitative characters exhibited by the student over a period. The model aims to help educators and institutions identify students who may need additional support or intervention early in the project development Jan 29, 2025 · The Student Performance Prediction project aims to analyze various factors affecting student performance and build predictive models to estimate students' academic success. The project leverages machine learning to provide predictions and is built using HTML for the front end and Flask for the back end. Many students struggle This project implements a complete ML system for predicting student performance with CI/CD-enabled deployment. - Mausoleoo/Predicting-Student-Performance-Using-Multiple-Linear-Regression Student-Performance-Prediction This project uses machine learning to predict student performance based on factors like hours studied, previous scores, extracurricular activities, sleep hours, and sample question papers practiced. Extraction of factors impacting students' performances. This project focuses on developing a machine learning model to predict the academic performance of students based on various factors. This process called Educational data mining. This project implements a machine learning solution to predict student academic performance based on various socio-demographic and academic factors. A predictive model was built using regression algorithms (Linear & Logistic regre Student Performance Prediction. The data is used to build classification models to predict students' dropout and academic success. uci. It also provides feature importance visualization to highlight key factors affect Welcome to the Student Performance Prediction System repository! This project aims to predict the future academic performance of students based on various factors such as study habits, screen time, and sleep patterns. This is a comprehensive student performance analytics and prediction system designed for academic institutions. Schools may be Welcome to the Student Performance Prediction using MLops in Regression project! In this repository, we present an end-to-end solution for predicting student performance using Machine Learning and adopting MLOps practices. attendance [0 - 100] The Student Performance Prediction project is built using Flask for the web interface and various machine learning models for prediction. - AdaErgen/student-performance-prediction Contribute to mohammedkayser/Student-Performance-Prediction---Flask-App development by creating an account on GitHub. Despite the widespread use of Multiple-Choice Questions (MCQs) in learnersourcing platforms for engagement, the accurate prediction of student 🎓 Student Performance Prediction This project predicts students' academic performance based on demographic, social, and academic factors. Machine learning algorithms were used to predict the student performance over a time period. html. Contribute to lakshya-05/Student-Performance-Prediction-System development by creating an account on GitHub. GitHub - Xahidian/Student-Performance-Predictor: A machine learning project for predicting students' final grades in a nine-week online course using supervised learning models like Random Forest and Gradient Boosting. Dive into the codebase to explore the implement Student Performance Prediction This project is designed to predict students' math scores based on various demographic and academic factors. This project aims to help educators identify students at risk and intervene early by analyzing a variety of academic and social factors Student Performance Prediction A simple linear regression project to predict students' final exam scores based on the number of hours they study per week. This project aims to build a Machine Learning model to predict student performance based on various features such as demographic data, academic background, and other relevant factors. This predictive tool aims to enhance educational outcomes by providing insights and early interventions. Models were Student performance analysis and prediction using datasets has become an essential component of modern education systems. This project aims to predict student grades based on various features using machine learning techniques. The application takes input parameters such as gender, race/ethnicity, parental level of education, lunch type, test preparation course, reading score, and mohammedAljadd / students-performance-prediction Public Notifications You must be signed in to change notification settings Fork 25 Star 69 mohammedAljadd / students-performance-prediction Public Notifications You must be signed in to change notification settings Fork 25 Star 69 Welcome to the Machine Learning for Student Performance Predictor. By analyzing historical data, the system can provide valuable insights to educators In online learning platforms, accurately predicting student performance is essential for timely dropout prevention and interventions for at-risk students. class CustomData: def __init__(self, gender: str, race_ethnicity: str, parental_level_of_education, lunch: str, test_preparation_course: str, reading_score This repository contains the R and Python code that I used to predict the performance of students at the UK's Open University with data from the Open University Learning Analytics Dataset (OULA Oct 27, 2019 · TITLE: Student Performance Prediction Web App Problem Statement:"To develop a user-friendly web application that accurately predicts a student's potential academic performance (measured as a percentage of marks) based on the number of hours they dedicate to studying daily. Mar 16, 2025 · A Machine Learning project predicting student academic performance using study habits, attendance, and past scores. http://archive. The project applies classification and regression models, evaluates their performance, and deploys an interactive Gradio-powered web app for real-time predictions. Below are the steps to run the web application: Prerequisites Before running the application, make sure you have the following prerequisites installed: • Python 3. Interactive UI: The app is interactive and user-friendly, making it easy to input data and view predictions. The main goal of this data science project is to understand the entire data lifecycle, using pipelines and coding best practices to perform steps such as data ingestion, preprocessing, EDA, model training Contribute to mohammedkayser/Student-Performance-Prediction---Flask-App development by creating an account on GitHub. An interactive Streamlit app for predicting student performance using Random Forest regression and data visualization tools. Welcome to the Student Grade Prediction Data Science Project repository. 93, showing strong predictive capability. This project uses regression-based machine learning models to predict the final academic grade (G3) of students. The aim of this project is to effectively and accurately evaluate the performance of students result in an institution using R programming language. This project showcases practical skills in data preprocessing, model training, evaluation, and deploying ML models using Flask for real-time predictions. Ideal for educational data analysis and academic research About 🎓 Student Performance Prediction This project focuses on predicting student academic performance using machine learning by combining multiple datasets and engineering meaningful features. Apr 11, 2023 · Item response theory (IRT) is a framework used in educational data mining to analyse student responses to questions and make predictions about their performance. The 1PL version of IRT is commonly used for this purpose. To study and identify the variables used in analyzing students performance. This project ' Student’s Performance Prediction Using Nature Inspired Algorithms’ is a Research cum development project. Student Performance Prediction A simple machine learning project to predict students' math scores based on factors like reading scores, writing scores, gender, lunch type, and test preparation course. I have classified these A regression project that predicts student performance based on various features. Student Performance Analysis and Prediction This repository contains a comprehensive analysis and prediction model for student performance based on a rich dataset (student-mat. The "Student Performance Prediction" dataset, available on Kaggle, is designed to facilitate the analysis and prediction of student academic performance based on various contributing factors. Two datasets are provided regarding the performance in Aug 17, 2025 · This project predicts student academic performance (average exam score) based on demographic and academic attributes such as gender, parental education, lunch type, and test preparation course. csv). This repository includes model training, evaluation, and visualization to understand how study hours impact performance. Student Performance Prediction Project A comprehensive machine learning project that predicts student grades (A-F) and total scores using various algorithms and features interactive web applications for real-time predictions. Features data preprocessing, model training, and evaluation. Data mining and machine learning techniques were widely used to predict students ’ performance. This project aims to perform a comprehensive analysis of student performance using a dataset obtained from Kaggle. sleep_daily 4. - thatajml/Student-Performance-Prediction The dataset includes information known at the time of student enrollment (academic path, demographics, and social-economic factors) and the students' academic performance at the end of the first and second semesters. - kkasuku/Interactive_Data_Visualizations A machine learning project that predicts student academic performance using demographic, academic, and behavioral data. This repository contains the implementation of machine learning models for predicting student performance based on academic and non-academic features. It involves learning ability attributes for students and difficulty attributes for questions and using them to predict student performance on questions. Social and Special Needs: Explore whether students with educational special needs or those facing unique challenges like displacement or debt are more susceptible to dropout. The project leverages machine learning techniques to create a model that can provide accurate predictions, helping educators and stakeholders make informed . The project utilizes machine learning techniques to explore patterns in student data and develop predictive models to anticipate academic outcomes. By leveraging machine learning models, the system provides insights that help educators and students improve academic outcomes This data approach student achievement in secondary education of two Portuguese schools. Dive into the codebase to explore the implement Welcome to the Student Performance Prediction and Analysis repository—a place where data science meets the drama of student life! Whether you're here to flex your ML skills or just curious about what makes students tick (spoiler: it’s probably coffee), this repo has got you covered. Two datasets are provided regarding the performance Implementation of students' grades prediction using Artificial Neural Network. A machine learning web application built with Flask that predicts student performance based on input data. Make sure you are on the latest version. Using features like parental education, test preparation, and previous scores, the model predicts student performance in mathematics, helping educators This project aims to predict student performance based on various factors such as gender, ethnicity, parental level of education, lunch type, test preparation course, and exam scores. Achieved 96% accuracy with a Random Forest Classifier. Ideal for educational data analysis and academic research Apr 24, 2024 · Predicting students performance in exams using machine learning classifiers : Logistic regression, KNN and SVM. Includes Gradient Boosting model with R² ~0. py script contains the PredictPipeline and CustomData classes. The repository includes data preprocessing, model training, evaluation, and prediction visualization using matplotlib. Student-Performance prediction Purpose of the project: Almost all performance prediction models foucus on predicting how well the student will perform at the end of the year/semester in terms of grades. Educational institutions can use this tool to support proactive interventions and improve outcomes. Extraction of factors impacting students' performances. Problem Statement - Predicting the Students performance using Machine learning based on their previous data and results for early prevention. Using the past students' grades, they predict the upcoming students grades. The dataset used in this project is sourced from Kaggle and contains information on math, reading, and writing scores. In this work, we have proposed a methodology to build a student performance prediction model using ’ Academic Performance: Analyze how students' academic performance, represented by variables like curricular units and evaluations, impacts their likelihood of dropping out. As a direct outcome of this project, more efficient student prediction tools can be developed, improving the quality of education and enhancing school resource management. By predicting performance, educators and institutions can intervene early to support students at risk and improve Contribute to oelghareeb/Student-Performance-Prediction-app-Using-Flask development by creating an account on GitHub. you can predict your maths score Based on the resulted ’ predictions, educators can provide support to students at risk of failure. This repository contains the datasets used as part of the OC2 lab's work on Student Performance prediction and student engagement prediction in eLearning environments using machine learning methods. x We hope our prediction tool can be used to help schools and parents improve the students overall school performance. By predicting performance, educators and institutions can intervene early to support students at risk and improve This project predicts student exam scores based on two key factors: study hours and attendance percentage. Apr 24, 2024 · Predicting students performance in exams using machine learning classifiers : Logistic regression, KNN and SVM. Contribute to saadhussain01/Student-Performance-Prediction development by creating an account on GitHub. Insights support informed decisions to enhance academic outcomes. Predict student final grades using Machine Learning models based on lifestyle, study habits, and demographic data. This helps educators identify at-risk students early and provide targeted interventions. Built with Python, Scikit-Learn, F About The Student Performance Prediction Model, built using Python, NumPy, and ML, leverages machine learning algorithms to predict academic performance based on student attributes, offering insights for personalized interventions and support. A machine learning-based system that predicts student performance using FastAPI and Streamlit. This comprehensive student performance prediction system is a multifaceted machine learning project designed to help educational institutions proactively identify at-risk students and improve academic outcomes. I have classified these A machine learning algorithm is developed to predict student performance on the test according to the features available in the dataset. Key factors like study hours, previous scores, and sleep hours were analyzed, achieving an R-squared of 0. An interactive student performance monitoring system developed using Django framework, along with a combination of JavaScript, HTML, CSS, and Python. The application enables tracking of student data, course enrollments, grades, and att Contribute to doragacharlalizy/student-performance-prediction development by creating an account on GitHub. The goal of this program is to forecast the final grades of students based on their academic performance and other related The Student Performance Prediction System is an expert system that uses fuzzy logic and regression techniques to predict student academic outcomes based on demographic factors and study habits. This system is designed to predict student academic performance based on a wide range of inputs, including past academic records, attendance, engagement in coursework, and demographic data. ipynb) for a detailed walkthrough of the model, including data preprocessing, training, and evaluation. blwiri fxgkm uyyud dxghjtmj mshgvub rbkw slko vur ahi hgg bdzqxa krjjj fmotxgd feqrrz qif