This project is an implementation of a machine learning model using LSTM to predict stock prices. The front-end of the application is built using Streamlit, and the back-end is built using FastAPI. The model is trained using historical stock data, and the predicted prices are displayed on a graphical user interface.

To run the application, first start the FastAPI server:

uvicorn app.main:app --reload

Then, in a separate terminal, start the Streamlit app:

streamlit run app.py

You should now be able to access the application in your web browser at http://localhost:8501.