This document discusses using machine learning algorithms to analyze data from a hydrogen gas power plant. It provides background on machine learning and describes using the Microsoft Azure Machine Learning Studio to build, test, and deploy a predictive model. The document outlines gathering data from a hydrogen gas power plant, cleaning the data, training a decision forest regression model on the data, and evaluating the results. The trained model is able to predict vehicle pressure and state of charge of hydrogen gas within a vehicle's storage system based on the analyzed data.