Streamlit Prediction Web App

This is a simple Streamlit web application designed to make predictions through a CSV file. The app supports both classification and regression tasks using various machine learning models.

Table of Contents

• Overview
• Features
• Requirements
• Installation
• Usage
• File Structure
• License

Overview

The web application is created using Streamlit, a Python library for creating web applications with minimal effort. The app allows users to upload a CSV file, preprocess the data, and perform either classification or regression tasks based on their selection.

Features

• Upload a CSV file
• Preprocess the data by removing outliers and handling missing values
• Perform classification tasks using Random Forest, Gradient Boosting, and Support Vector Machine models
• Perform regression tasks using Random Forest, Gradient Boosting, and Support Vector Machine models
• Display accuracy or mean squared error and other relevant metrics

Requirements

Make sure you have the following installed:

• Python
• Streamlit
• pandas
• scikit-learn

Installation

# Clone the repository
git clone https://github.com/Jeetanand/desicon_maker


# Change directory
cd desicon_maker

# Install dependencies
pip install -r requirements.txt

Run the App

streamlit run your_app.py

Replace your-username, your-repository, and your_app_name.py with your GitHub details and app file name.

Author

Abhijeet Anand