EduPredict Full Stack Analytics Dashboard | React, Flask, Hadoop & scikit-learn
EduPredict-v1 is a full-stack educational analytics platform I built for my final Aptech eProject. The goal of this platform is to leverage Machine Learning and Big Data to predict student dropout rates and forecast academic performance (GPA), allowing educators to identify at-risk students early.
In this video, I demonstrate the complete workflow: logging into the secure React frontend, exploring the interactive ECharts dashboards, and showing how the predictive Scikit-learn models deliver real-time insights processed through our Big Data pipeline.
🛠️ Technologies & Architecture Used:
Frontend: React, Vite, Tailwind CSS, ECharts (for interactive dashboards)
Backend & API: Python (Flask), JWT Authentication
Database: MongoDB
Big Data Processing: Hadoop HDFS & PySpark (handling large-scale educational datasets)
Machine Learning: Scikit-learn (Custom models for GPA forecasting and Dropout prediction)
💡 Key Project Highlights:
Engineered a robust end-to-end data pipeline connecting Hadoop HDFS to a React user interface.
Implemented complex Data Science concepts to train accurate prediction models.
Designed a responsive, user-friendly UI to make complex data readable for end-users.
Learned how to manage Full-Stack architecture securely and efficiently.
Thank you to my Aptech instructors and peers for their support throughout this journey! If you have any questions about the implementation or the architecture, feel free to ask in the comments!
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