Welcome to the repository of the Dow Jones Predictor, a project developed by students of Duale Hochschule Baden-Württemberg Mannheim. This project aims to leverage Python's powerful data analysis capabilities to predict the trends of the Dow Jones Industrial Average (DJIA) and is showcased through a user-friendly web app created with Streamlit.
The Dow Jones Predictor is a tool designed to analyze historical data of the DJIA and use machine learning algorithms to forecast its future trends. This project is part of our coursework at Duale Hochschule Baden-Württemberg Mannheim and serves as a practical application of our learning in data science and web development.
- Data Analysis: Utilizes Python for in-depth data analysis and processing.
- Machine Learning: Implements machine learning models for accurate predictions of the Dow Jones index.
- Interactive Web App: A Streamlit-based web interface that allows users to interact with the predictor and view graphical representations of data and predictions.
- User-Friendly Design: Easy-to-navigate UI, making it accessible for both technical and non-technical users.
To set up this project on your local machine, follow these steps:
- Clone the Repository:
git clone https://github.com/GermanPaul12/DataWhispers-Stock-Price-Prediction-Projekt-DHBW.git
- Navigate to the Project Directory:
cd DataWhispers-Stock-Price-Prediction-Projekt-DHBW - Install Required Packages:
pip install -r Code/requirements.txt
To run the Streamlit web app:
Either:
streamlit run Code/🏠_Home.pyAfter running the command, Streamlit will start the web server, and the app will be accessible in your web browser.
Or:
Click this link
- Use the navigation options in the Streamlit app to switch between different views.
- Interact with the provided controls to customize the data analysis and predictions.
- View the results displayed in charts and graphs for easy understanding.