Predict Performance Before the Exam (Streamlit App)

This is a simple, interactive web app built using Streamlit and Scikit-learn that predicts a student's likely performance before an exam based on behavioral and preparation factors.

But let’s take a moment to reflect on this project...

Often, we follow a learning journey focused on mastering specific topics — and eventually take an exam to prove our skills.

But it’s no secret that within what’s effective, there’s always something more efficient.

A car can get you from one state to another, just like a plane can — but when it comes to efficiency, the plane wins.

That’s exactly the idea behind this project: making the exam prep journey more efficient. How? By analyzing your study habits, sleep quality, routines, motivation, and more!

This tool uses a machine learning model I trained — still in its early (and far from final) version 😅 — but it already provides useful insights for self-assessment.

Key points:

• You don’t need this model — it’s just an aid.
• The result is a projection, not a definitive answer.
• It helps identify areas to improve.
• It's great for self-reflection.
• It’s open source — contributions welcome!

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📁 Files Needed

Place all the following files in the same folder:

├── app.py
├── human_verification.py
├── trained_performance_model.joblib
├── requirements.txt

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⚙️ How to Run the App Locally

1. Clone or Copy the Files

If not using Git, just upload/copy the files into a project folder.

2. Create a Virtual Environment (Optional but Recommended)

python3 -m venv venv
source venv/bin/activate  # On Windows use: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Run the App

streamlit run app.py

The app will be accessible at: http://localhost:8501

Predict Your Score Online

1. Instructions and Access the Link

• This is the Beta version
• Available daily from 10 AM to 7 PM (UTC-3 / Brasília Time)
• You can test it once per day
• Live App: Try it here

2. Solve a challenge to prove you are a human
   Solve the clock chanllenge to get form access:

3. Provide Your Information
   Enter your basic personal and study-related details, then click the Predict Performance button. A Linear Regression model will analyze your inputs to estimate your exam score:

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4. Get an Approximate Score
   You'll receive a predicted performance percentage with a good advice:

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