Overview

The project revolves around creating a dynamic web application designed for predicting stock prices using various machine learning algorithms. By harnessing the power of frameworks like Django and Bootstrap, alongside databases such as SQLite, this application seamlessly integrates real-time data from Yahoo Finance, enabling users to make informed predictions based on historical stock performance. Whether you're a budding investor or a seasoned trader, this application offers a robust approach to stock price forecasting.

Features

Real-Time Data Display: The home page showcases live stock prices, providing users instant insight into current market conditions.
Prediction Functionality: Users can input ticker symbols and specify the number of days for prediction, allowing for tailored forecasting.
Unique QR Code Generation: After predictions are made, the app generates a QR code linking to the predicted results, enhancing accessibility.
Interactive Graphs: The application visualizes data through graphs that compare real-time stock prices with predicted values, aiding in better understanding.
User-Friendly Interface: Designed using Adobe XD and Figma, the application boasts an intuitive layout that enhances user experience.
Multi-Platform Compatibility: The app has been tested on MacOS, Ubuntu, and Windows, ensuring broad accessibility for users across different operating systems.
Django Framework Utilization: Leverages the Django framework for a robust backend, ensuring that the application runs smoothly and efficiently.
Easy Project Installation: Clear step-by-step instructions are provided for cloning the repository and setting up the virtual environment, making it accessible for both novice and experienced developers.

Kumar Laxmi

Stock Prediction System Application