This is the second part of the project. In this example, the XGBoost algorithm is trained using the asset's data in OHLC format with just one change, which is the creation of a new "Close_Tomorrow" column to help predict the next close of the paper after the initial training.
This part of the project is just an example of how it is possible to use the XBoost algorithm to make predictions based on historical data and how to work with the Streamlit tool to display the analyzed data. There is no recommendation to buy or sell assets, and the project is generally educational, so I don't recommend using it to make any financial decisions before checking several points.
All the libraries used to run this part of the project are already described in the main README where I explain all the parts of the project, the link to the file is below: