I am an absolute beginner in field of machine learning, I started doing titanic assignment in Kaggle and found(read some where) Random Forest is the best fit. I started reading about random forest and found the Explanation by Edwin Chen in this question intuitive. This made me "understand" how I can solve the Titanic assignment which predicts if one survives or not(classification). But I cannot understand How random Forest will work for regression which is continuous.
Please don't mind to point out any mistakes in my assumptions or the way I started things. Any advice would be helpful, This looks very vast and Don't even know where to begin.