Nemanjavuk69
Junior Member
- Joined
- Mar 23, 2022
- Messages
- 71
I am currently following a long this video, which is an introduction to Machine Learning. (
)
At 47:15 to 48:45 the professor goes on to talk about, how "non normalizing" (sorry, I have a hard time hearing him even with subtitles on its a mess) the dimension of the vector goes down by 1. So having a vector in the realm of [imath]R^p[/imath] gives a dimension of [imath]R^{p-1}[/imath]. He even uses the example of if a vector was in [imath]R^2[/imath] than it would be [imath]R^1[/imath]. This seems wrong, but it might be me who have a hard time understanding him. Can someone brighter than me shine some lights on this? Thank you very much.
At 47:15 to 48:45 the professor goes on to talk about, how "non normalizing" (sorry, I have a hard time hearing him even with subtitles on its a mess) the dimension of the vector goes down by 1. So having a vector in the realm of [imath]R^p[/imath] gives a dimension of [imath]R^{p-1}[/imath]. He even uses the example of if a vector was in [imath]R^2[/imath] than it would be [imath]R^1[/imath]. This seems wrong, but it might be me who have a hard time understanding him. Can someone brighter than me shine some lights on this? Thank you very much.