https://github.com/shubhamdutta2000/student-performance-analysis

Analyse performance of students on the basis of their personal life style, studying style, family related, educational environment satisfaction, students grades using ML model
https://github.com/shubhamdutta2000/student-performance-analysis

boxplot factors grades jupyter-notebook logistic-regression machine-learning python3 students students-performance

Last synced: about 19 hours ago
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Analyse performance of students on the basis of their personal life style, studying style, family related, educational environment satisfaction, students grades using ML model

• Host: GitHub
• URL: https://github.com/shubhamdutta2000/student-performance-analysis
• Owner: Shubhamdutta2000
• License: mit
• Created: 2020-11-28T12:46:07.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2020-12-01T06:11:41.000Z (almost 4 years ago)
• Last Synced: 2023-03-06T05:36:02.954Z (over 1 year ago)
• Topics: boxplot, factors, grades, jupyter-notebook, logistic-regression, machine-learning, python3, students, students-performance
• Language: Jupyter Notebook
• Homepage:
• Size: 840 KB
• Stars: 1
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Student-Performance-Analysis

## INTRODUCTION

Machine learning is the study of computer algorithms that improve automatically through experience. The algorithms build a model on sample data known as “training data”, in order to make predictions or decisions without being explicitly programmed to do so. It is sometimes related to computational analysis, and it is also referred as predictive analysis.

## AIM OF OUR PROJECT:

The aim of our project is to develop a regression model where the performance of the students are predicted not only on mere grades, but also other non educational factors including their personal life, their dedication to studies and other factors. For this model, two sets of data were taken from schools from Portugal. We tried to make our project with clean data, and after that we used logistic regression which looked on overall actors and finally predicted which students would perform better. In this way, special attention can be delivered to those who needed them.

## Model:

We tried to analyze the students performance based on the given attributes and finally using logistic regression, We tried to predict whether the student will pass or fail in the exam.

Note : In the training and prediction, We've not included previous grades, since they directly affect the final grades.

## Install All packages

     pip install -r requirements.txt