🖥️ Stock Price Prediction GUI App

🎯 Overview

This project is a Desktop GUI Application built using Tkinter, designed to demonstrate how Machine Learning models can be integrated into user-friendly interfaces. Users can input stock-related data and receive immediate predictions for the day's highest and lowest prices of selected banks.

While the data is based on stock prices, this project mainly showcases the power of Python GUI development using Tkinter.

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💡 Key Features

• 📊 Interactive GUI: Built entirely in Tkinter for seamless user interaction.
• 🧠 Backend ML Model: A simple Linear Regression model trained on historical bank stock prices.
• 🧾 Database Integration: Uses MySQL to store each prediction made via the app.
• 📤 User Inputs: Select bank name, enter date, previous close, and opening value.
• 📈 Live Results: Instantly see the predicted high and low values for the given input.

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🧩 Tech Stack

Component	Technology
GUI Framework	Tkinter
ML Model	Linear Regression (Scikit-learn)
Data Handling	Pandas, NumPy
Database	MySQL
IDE Used	Spyder

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🖼️ Application Interface

🧑‍💼 Input Fields:

• Bank Name (Dropdown)
• Year, Month, Day
• Previous Close Price
• Opening Price

📤 Output:

• Displays predicted High and Low values
• Automatically saves inputs and results into MySQL

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🔧 How It Works

1. Startup: Launches a Tkinter window with labeled input fields.
2. Data Entry: User selects/enters stock-related values.
3. Prediction: On clicking "Check High/Low", the model processes the input.
4. Result Display: Predicted High/Low prices are shown below the button.
5. Database Logging: The result and input data are saved into a MySQL table.

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🔐 Sample Code Snippet

b1 = Button(root, text="Check High/Low", bg="slateGray2", width=20, font=("bold",10), command=get_data)
b1.grid()