Stock Market Prediction Web App Using Machine Learning And Sentiment Analysis

Overview

The Stock Market Prediction Web App harnesses the power of Machine Learning and sentiment analysis to provide users with insightful predictions about stock prices. By integrating data from popular social media platforms and utilizing complex algorithms, this web application aims to assist both novice and seasoned investors in making informed decisions regarding their investments in stocks listed on NASDAQ or NSE. The project effectively combines the front-end technologies of Flask and WordPress to create a user-friendly interface.

This innovative app allows users to input stock symbols and receive forecasts for the next seven days, all while considering market sentiment derived from social media tweets. With robust features and a flexible backend, this app not only caters to the needs of users but also empowers administrators to manage the system effectively.

Features

• Prediction Algorithms: Utilizes ARIMA, LSTM, and Linear Regression to forecast stock prices for the upcoming week, providing multiple analytical perspectives.
• Sentiment Analysis: Integrates social media sentiment to enhance the accuracy of stock predictions, offering a holistic view of market trends.
• User Roles: Features two distinct roles, Admin and User, allowing for effective management and access control within the application.
• Easy Installation: Straightforward installation process with clear instructions, making it accessible for users with varying technical skills.
• Interactive Front-End: Developed using Flask and WordPress, ensuring a seamless user experience with easy navigation and interaction.
• Comprehensive Documentation: Includes detailed setup instructions and system requirements, aiding users in getting the app up and running quickly.
• Demo Access: Provides a demonstration with admin credentials to allow potential users to explore the app's functionalities before committing to its use.