Hello every one ,
Im new to this site and ml course ,
I am currently studying regression using table data.
I was studying the XGBoost algorithm in the hope that it would be useful when modeling, but I suddenly wondered why I should know the algorithm.
If you know the following contents, you will not be troubled to use it, and I wonder if there is no point in learning algorithms.
What kind of scene can use XGBoost
What kind of distribution should the input data have?
What are the characteristics
When is it often used
Similarly, the question of whether studying algorithms really helps modeling?