Stock Price Prediction Web App Using Python & Flask Real-Time

Stock Price Prediction

Machine learning is very useful in many fields, as it helps do tasks automatically that people used to do manually. One such use is predicting if buying a stock will be a good idea or not.In this article, we’ll learn how to predict a signal that shows whether buying a particular stock will be profitable using machine learning.

Let’s Start by Importing Libraries

Python has some great libraries that make data handling and ML tasks much easier. We can do complex tasks with just a few lines of code.

Here are the libraries we’ll use:

• Pandas – Used to load and manage data in a table-like format (DataFrame).

• Numpy – Helps with fast calculations using arrays.

• Matplotlib / Seaborn – For creating graphs and visualizing data.

• Sklearn – Has many built-in tools for data processing, building ML models, and testing them.

• XGBoost – A strong ML algorithm that helps get high accuracy in predictions.

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 Project Details

Available Features

•  Real-Time Stock Data
•  Downloadable Stock History in CSV Format
•  Visual Price Charts & Volume Analysis
•  Company Financial Summary (Market Cap, PE Ratio, Dividend Yield, etc.)
•  API Endpoint for Integration
• Flask-Based Web Security with Error Handling

 Technology Stack

• Language: Python
• Framework: Flask
• Libraries: yFinance, Pandas, Flask, Jinja2
• Front-End: HTML (Flask templating)