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
| Project Name | Language |
|---|---|
| Stock Price Prediction with Machine Learning | Python (Django Framework) |
| Database | SQLite |
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:
- Real-time Stock Data Fetching – Live price updates directly on the home page.
- Stock Price Prediction – Predicts future prices based on user-selected days.
- Detailed Ticker Information – Lists all supported stock tickers with essential details.
- Interactive Graphs – Visual display of both historical and forecasted data.
- QR Code Generation – Unique QR code for quick result sharing and mobile access.
- 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
stock-price-prediction using machine learning github
stock price prediction using machine learning project report pdf
stock price prediction using machine learning research paper
stock-price-prediction github
stock market prediction project in python pdf
stock price prediction using machine learning project ppt
stock price prediction project source code
stock price prediction project pdf
stock price prediction with machine learning professional django web app github
