🧩 The Stock Market Recommender

📖 Project Overview

The Stock Market Recommender is a graduation project that aims to develop an intelligent stock recommendation system using machine learning and deep learning techniques. The system analyzes historical stock data, technical indicators, and financial trends to provide accurate predictions and assist investors in making informed decisions.

🎯 Objectives

• Integrate machine learning algorithms to enhance stock price prediction.

• Use deep learning models to improve accuracy and reliability.

• Collect and preprocess historical stock price data from reliable sources.

• Design a user-friendly web interface for easy use by investors of all experience levels.

• Develop a robust and interactive stock recommendation platform.

🛠 Tools & Technologies

• Programming Languages: Python, HTML, CSS, JavaScript

• Machine Learning Frameworks: TensorFlow, Scikit-learn

• Database: MySQL

• Development Environment: Jupyter Notebook, Google Colab

👥 Team Members

• Haneen Ahmad Alqahtany

• Shahad Abdullah

• Shahad Hassan Asiri

• Saja Asiri

Supervised by: Ms. Mona Mushabab

💡 Project Summary

This project seeks to revolutionize stock price prediction by combining machine learning and deep learning with real historical data. The platform aims to improve prediction accuracy, reduce risks, and empower investors to navigate the financial market with confidence.