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The "Comprehensive Student Performance Analytics" project emerges as a pioneering initiative poised to revolutionize how educational data is harnessed and translated into actionable insights

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Comprehensice Student Performance Analytics

A tool to merge education and data science by using ReactJS and Neo4j’s graph database. It empowers educators with actionable insights for informed decisions by integrating diverse data sources!

Current Features

  • Linear Regression - Relationship between Study Hours and Marks Scored.
  • Logistic Regression - To predict Probability of Passing on Previous marks scored.
  • Time Series Forecasting - Used data of JEE Mains ranks from 2013-2019 to predict 2020-2024.
  • Random Forest - To calculate Actual vs Predicted GPA.
  • Demographics - Gender Ratio and Geographic ratios to calculate Most and Least Consistence Students.
  • Past 10 Years Trends

Screenshots

  • Start Page Animation

Dashboard

  • Login Page

Companies

  • Linear Regression

Topics

  • Search Students

CompanyPage

  • Demographics

TopicPage

  • Comparison Analysis

CompanyPage

  • Time Series Forecasting

TopicPage

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The "Comprehensive Student Performance Analytics" project emerges as a pioneering initiative poised to revolutionize how educational data is harnessed and translated into actionable insights

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