Support Vector Machines Part 2: The Polynomial Kernel (Part 2 of 3)

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Support Vector Machines use kernel functions to do all the hard work and this StatQuest dives deep into one of the most popular: The Polynomial Kernel. We talk about the parameter values and how they calculate high-dimensional coordinates via the dot-product and high-dimensional relationships

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Your videos should be mandatory tutorial for Data Science/ ML courses in all the Universities. Students throughout the world would get benefited after watching the best ML video.Hats off to you great Josh

RHONSON
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Best machine learning playlist I have encountered on the YouTube .
The animations and your funny way of teaching makes it easy to understand concepts.
The amount of work you put to create these videos deserves great appreciation.
I would definitely recommend to go through the videos for anyone who is reading this comment.

Snoozy_FTW
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Dude, You are amazing. The best tutorial on SVM. I have searched the entire Internet to understand but couldn't. Please continue to make videos.

madhuvarun
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I will make it easy for you guys:

3:38 - BAM
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stanlukash
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Bro you're just a blessing. Never stop with the dry humor. Lot's of love for you!

itsfabiolous
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I want to thank you so much for all your videos. I was lost in a forest of vectors matrices and greek letters when I heard about these topics in lecture and I did not understand a thing. As I was practising for the exam, I discovered your videos and now I do actually understand what is happening. Really love the practical, example driven approach!

marcoharfe
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I have read and looked at most recommended books and videos on kernels and whilst somewhat familiar with the math, never truly understood the principles.

Statquest actually makes complex topics simple, arguably one of the best if not the best teacher on youtube and definitely the best stat explanations.

Thanks Josh much appreciated 👍

jacobwalker
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This is one of the best explanation for support vector machines... If anyone is interested in why dot products are integral to the idea of SVM, please refer to Professor Wilson's MIT lecture on SVM... It is another great explanation for SVM...

priyangkumarpatel
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First of all, thanks for your explanation, after plugging two data points into polynomial kernel function a and b then get the value 16, 002.25, then you said we get higher dimensional relationship. Could you elaborate further what "relationship" did you refer to based on the value 16, 002.25? Sorry I was not quite sure about that

MrZidane
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What do you mean by high dimension relationship??

ahming
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I have grown to love your little songs. They sound like Pheobe's songs!!! I have a little question, what do you use for visualization?

deashehu
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My man. I'm so happy I have my presentation about SVM's after your uploads... Keep up the great work!

jonathannoll
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Sir, this is the best video for explaining the Kernel!

chenghuang
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I really appreciate how the way it is explained. Please keep on the good job!

kwok
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This is how concepts should be introduced to students.. makes so much more sense

johnjunhyukjung
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You are videos are simply amazing! And the level of abstraction is right at the sweet spot! Thank you for the extremely thoughtful and precise illustrations!

Add
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thank you a lot you are such a big help in this harsh student world god bless you .

amalboussere
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rrrprogram
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Mr. Starmer almost unconsciously changing machine Learning's future 😀

muhtasirimran
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You literally saved my homework with your videos

evelillac