The document describes using LSTM and ARMA deep learning algorithms to forecast crude oil prices. It uses historical crude oil price data from QUANDL to train models for each algorithm and predicts future prices. The LSTM model achieves better prediction accuracy than the ARMA model according to a displayed graph. The project allows loading the crude oil dataset, running each algorithm to generate a model and predict prices, and compares the prediction accuracy between the two algorithms.