Model Selection and Train/Validation/Test Sets - Stanford University | Coursera:
At 10:59~11:10
One final note: I should say that in the machine learning as of this practice today, there aren't many people that will do that early thing that I talked about, and said that, you know...
Is my comprehension correct? Because English subtitles on coursera sometimes are not correct. As I konw, here what Chinese subtitle means is opposite to what English one does. So I am not sure whether Andrew Ng said "there aren't" or "there are"
Thanks for your reading.
I would like to ask another one.
Diagnosing Bias vs. Variance - Stanford University | Coursera:
At 02:34~02:36, what Andrew Ng said is not quite clear as well as the English subtitle.
My comprehension is as following
If d equals 1,.... to be high training error.
It's not that complete.
Would anyone like to identify that?
Thank you...