Interactive Prediction App Live

Overview

This Streamlit app provides interactive prediction capabilities for two key tasks:

1. Predict Student Scores: Analyze student performance based on hours of study.
2. Predict Iris Species: Classify iris species based on measurements including Sepal Length, Sepal Width, Petal Length, and Petal Width.

Prerequisites

Ensure you have Python installed on your system. You can download Python from python.org.

Installation

1. Clone the Repository (if applicable):

   git clone https://github.com/Charitra-1/GRIP-TASK.git
   cd GRIP-TASK

2. Create a Virtual Environment (optional but recommended):

   python -m venv venv

3. Activate the Virtual Environment:

   • On Windows:

     venv\Scripts\activate

   • On macOS/Linux:

     source venv/bin/activate

4. Install Dependencies:

   pip install streamlit pandas scikit-learn matplotlib seaborn

Running the Streamlit App

1. Navigate to the App Directory (if needed):

   cd GRIP-TASK

2. Run the Streamlit App:

   streamlit run main.py

3. View the App: You can now view your Streamlit app in your browser:

   Local URL: http://localhost:8501

Notes

• Ensure that you have all required dependencies installed before running the app.
• For any issues or feature requests, please refer to the project's issue tracker or contact the maintainers.