Stock Price Prediction with Machine Learning – Professional Django Web App

Stock Price Prediction

Introduction

Stock Price Prediction with Machine Learning is a fully functional web application that provides real-time stock market insights along with accurate price predictions. It is built using Django, a popular Python web framework, and uses Multiple Linear Regression—a machine learning algorithm that analyzes multiple factors to forecast stock prices.With its simple, user-friendly interface and strong backend processing, the application makes it easier for users to understand market trends and plan their investments wisely. Whether you’re a beginner learning about stock markets or an investor looking for reliable data, this tool offers a balance of simplicity and powerful features to support informed decision-making.

The home page of the application provides live market data fetched directly from trusted APIs.
To predict stock prices, simply go to the Prediction Page, enter:

• A valid stock ticker (e.g., AAPL, TSLA, MSFT)
• The number of future days you want to forecast

Click the Predict button, and you’ll instantly get:

• The predicted stock price
• Detailed company/ticker information
• A QR Code for quick result sharing

Two interactive graphs make the predictions visually clear:

• Left graph – real-time stock price for the past day
• Right graph – predicted stock price for the chosen future period

Additionally, the Ticker Info Page lists all valid stock tickers accepted by the system with comprehensive details.

Download New Real Time Projects :-Click here

Aim

To predict stock prices based on real-time data values fetched from an API, enabling users to make informed trading and investment decisions.

Objective

Develop a web application capable of:

• Fetching real-time stock market data
• Predicting stock prices using machine learning algorithms
• Displaying historical and predicted price trends with clear visuals

Scope

This application can be integrated into:

• Financial service platforms
• Business investment dashboards
• Educational tools for finance and data science learning
  It serves as a powerful decision-support system for analysts, traders, and business organizations.

Technology Used

Development Stack

• Languages: HTML, CSS, JavaScript, Python
• Frameworks: Django, Bootstrap
• Machine Learning: Multiple Linear Regression
• Libraries: NumPy, Pandas, scikit-learn
• Database: SQLite
• APIs: Yahoo Finance API, REST API
• IDE: VS Code, Jupyter Notebook

Available Features

Based on the project’s source files, the application includes:

1. Real-time Stock Data Fetching – Live price updates directly on the home page.
2. Stock Price Prediction – Predicts future prices based on user-selected days.
3. Detailed Ticker Information – Lists all supported stock tickers with essential details.
4. Interactive Graphs – Visual display of both historical and forecasted data.
5. QR Code Generation – Unique QR code for quick result sharing and mobile access.
6. User-Friendly Interface – Clean Bootstrap-powered design for easy navigation.

Project Installation

STEP 1: Create a virtual environment (Windows):

python -m venv virtualenv

STEP 2: Activate the virtual environment (Windows):

virtualenv\Scripts\activate

STEP 3: Install the dependencies:

pip install -r requirements.txt

STEP 4: Apply database migrations:

python manage.py migrate

STEP 5: Run the application:

python manage.py runserver

We have projects Available in all languages:–Click Here