I had a rough look at the contents of this course and have found that it deals with Random Forest and Deep Learning. So for those who have completed a Deep learning course, this course is actually a Random Forest course.
And since we can now do deep learning using tabular data, so why use Random Forest?
Jeremy said that when he tries to approach problems himself, then some problems are better on tabular deep learning, and some problems are better on Random Forest. But in this mention, I sort of feel that the difference would be an accuracy 1% or something. If not for the purpose of winning the competition, it’s not a big difference, is it?
If the purpose of using deep learning is making, it would be inefficient to spend time learning Random Forest or other machine learning methods. What do you think?