Logistic regression 5.2: Multiclass - Softmax regression

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Errata:
1:50 - Each of individual output probabilities depend on all the weights W, not just the weights of that element. So the first output probability doesn't only depend on w_1, but on W. And similarly for all the other elements.

Herman Kamper

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the whole logistic regression playlist is o good. great job!

blessontomjoseph

Thank you very much, it helped me a lot for my university classes. Very clear explanation. :)

Nanona

Very clear and concrete explanation! Thank you so much.

catdonut

Thank you for explaining the whole concept in a much simpler way.

gautamkulkarni

Your videos are quite easy to comprehend. Good job.

DimiqBaba

What an awesome video, thank you! I made sure to watch lots of ads for you, even though it probably doesnt make a difference :D

norebar

love it! so well explained and love the mathmetical proof

bnmsitc

Fantastic explanation, thanks a lot Herman!

ptnpdrs

This is a remarkable explanation, simple and complete, thank you very much !

lima

thank you for the explanation,
Better than the professor at University ! ...

mohamadalipour

Thanks, this is a very helpful video. One question, in the video you mentioned that since probability is between 0 and 1 and probabilities sum to 1, you need to raise e to the power of each score and divide by the sum of the scores to obtain a probability. Is there a reason that you choose e as the base of the exponent? Why not choose another number? My confusion is that if I chose a number like 10 as the base, I'm pretty sure my softmax model would classify everything the same as if I had chosen e, but that the probabilities calculated would be different. I'm wondering if softmax is actually returning the real probability, or just a number between 0 and1 that behaves like the real probability. Thanks!

Charles_Reid

Prof. Herman, i have an issue for this can i sent to your email please ?

israalewaa

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