We will use cross validation to know which kernel would be best for us . Otherwise we have to get the Business logic to guess and appropriate relationship in feature space and then from this intuition we will get to know by ourselves which kernel would be best.
3:27 If the vector is of d length that how does dot product take O(d square ) time? It should be O(d), Shouldn't it be? O(n) for multiplication , O(n) for addition Total = O(n)+O(n)=O(n) Can anyone explain?
This video is highly underrated!
It has helped a lot in getting known with kernels.
Efforts are greatly appreciated.
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Very Nice Video Maam. Thank you
Brilliant Lecture!
Superb; great video
A very useful lecture. Thank you
thank you!
very useful
Tanks for your video But how to choose the right kernel for your problem ? is there some criteria to decide what one you should choose?
Suppose consider two class which can be linearly separable then you will consider linear kernal function
We will use cross validation to know which kernel would be best for us . Otherwise we have to get the Business logic to guess and appropriate relationship in feature space and then from this intuition we will get to know by ourselves which kernel would be best.
Thank you sooooooooooooooo muchhhhhhhhhhhhh
3:27
If the vector is of d length that how does dot product take O(d square ) time?
It should be O(d), Shouldn't it be?
O(n) for multiplication , O(n) for addition
Total = O(n)+O(n)=O(n)
Can anyone explain?
Same doubt. Did you get the answer?
kennel function??😂😂 in the title...
watch at 1.5x and thank me later