In this topic we would implement **Random Forest Regression**, using Python. We would try to understand practical application of Random Forest and codes used for regression. As we have understood in our previous topic a random forest regression is a group of decision trees.

Step 1: Import the Libraries. We would use three libraries for this analysis:

- numpy
- pyplot
- pandas

Use below command to import the libraries.

Step 2: Import the data set.

Step 3: Fitting Random Forest Regression to the data set

Step 4: Predicting a new result

Step 5: Visualizing the Random Forest Regression results