A very basic implementation of Random Forest Regression in python. The sklearn.ensemble library is used to import the RandomForestRegressor class. The object of the class is created and is given a given an n_estimators value of 300. The n_estimator value is the number of Decision Tree Regression models to be included into the Random Forest Regressor model. The higer the value of the n_estimator, the more Decision Tree models added. And the more Decision Tree models added, the better the model is at predicting values of the dataset.