Hidden Talent AI

Project Overview

Hidden Talent AI predicts a student’s talent cluster based on learning behavior. By analyzing features like problem-solving time, study hours, error rate, improvement rate, task-switching frequency, and retry count, it provides insights into hidden strengths.

This interactive web app helps educators and learners identify potential and optimize learning strategies.

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Features

• Predicts student talent clusters using a trained Random Forest Classifier
• Interactive Streamlit web interface for inputting student behavior data
• Instant predictions to reveal strengths and areas for improvement
• Feature importance insights to understand what drives talent predictions

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Technologies Used

• Python – Programming language
• Pandas & NumPy – Data processing and manipulation
• Scikit-learn – Machine learning (Random Forest Classifier)
• Streamlit – Interactive web application
• Pickle – Saving and loading the trained model

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Installation

1. Clone the repository:

git clone
https://github.com/Suhani-ai-dev/HiddenTalentAI.git cd HiddenTalentAI