Thank you so much for making these videos Oscar! I am watching this a year from when you've released it (today is 6/17/2018) because I have just been introduced to deep learning and want to dig deeper into AI. These have been very helpful, thanks a lot!
Thanks so much for this video! You explained a pretty tricky topic in an intuitive and easily graspable fashion, without pushing out the technical details! I'm subscribing.
how could plot the class variable? Suppose the dataset has M1,M2,M3 and class variable attributes or Features. Then how could plot in hyperplan? pls explain me
Thanks, Oscar, the introduction of a third dimension which squares one of the variables was quite enlightening! My question: You showed classification but how does this relate to regression? I.e. what are the two classes when regressing y on x1?
good crisp and clear explanation .. Hey Oscar could you please upload videos for SVM with some real-time examples specially for 3D space data-set. Thanks
Great video, Oscar! I'm pretty sure, you'll get more subscribers if you could deliver some nice animation / 3D visualization about these machine learning concept. Because to be able to visualize in your head is the key to understand these concepts of machine learning. For example, I finally understand about kernel after I watched another video on youtube. However, I would not understand the concept though, if I did not watch your video in the first place. Your video elaborates better concept than that video even though that video illustrates with a nice 3D animation. Anyway, nice video projects! I hope you'll make more video about these machine learning in the future. Worth than several hours spent in a AI class. cheers!
The content is helpful but it would be even more helpful if you made it more clear. Like you were looking into something other than your iPad at 10:40. I don't think that's a good practice while explaining. No offense. Just a piece of advice. :)
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is there any of ur video which explains svm regression and other few
common regression algorithms? If yes please share me the link.
Thank you so much for making these videos Oscar! I am watching this a year from when you've released it (today is 6/17/2018) because I have just been introduced to deep learning and want to dig deeper into AI. These have been very helpful, thanks a lot!
Hey, great insight into SVM, thanks, man!
Glad to help :)
Fantastic explanation! Thank you for this.
Glad to help Jenny!
I found this very helpful, thanks. I would love to see some videos about semi-supervised learning.
I'm glad to hear! I'll look into it! :)
Thanks so much for this video! You explained a pretty tricky topic in an intuitive and easily graspable fashion, without pushing out the technical details! I'm subscribing.
The name of the video is precise. You do make it easy and understandable. Thanks a lot mate
Thanks a bunch Laurits, glad I could help!
is there any of ur video which explains svm regression and other few common regression algorithms? If yes please share me the link.
i'm so grateful it was really easy to understand SVM.
Subscribed. Thank you, this was short, clear and instructive.
Glad that you liked it Sabrina! I don't talk much about machine learning here any longer, so write to me on Facebook if you have any questions 😊
Awesome Tutorial !! Can you tell the difference between SVMs and structured SVMs or suggest me where to read ?
Hey bro! Don't know too much about structured SVMs unfortunately
Great summary Oscar. Just wondering how the dot product of vectors is involved in the SVM definitions. Thanks!
If I recall things correctly, the dot product defines the width of the margin from the hyperplane w :)
Great explanation of SVM!
Thanks Kurt!
Thanks for the video!! I really understood the key concepts!!
How can i used on trained set of SVM for classification of other data set
Very technical and clear! Awesome!
Great video, now understand basic concept of it
Good explanation for beginner to ML - SVM algorithm.
Thank you so much Oscar. It was Really Great. :)
Glad you liked it!
could you please upload some practical examples of use with SVM ??
how could plot the class variable?
Suppose the dataset has M1,M2,M3 and class variable attributes or Features. Then how could plot in hyperplan?
pls explain me
Hey Oscar! Can you do an intuition on backpropagation and how its actually working?
Hey Abhishek! Not uploading that much ML content any longer, but there are heaps of resources out there!
this really helps when bring the 2d to 3d ,obviously Oscar is not super good at hand drawing 3d pics ,but I really got the point
Haha yes it's quite obvious indeed. Great that you got the point! Glad that I could help
Thank you soo much for explaining , i have finally understood it ,great job
Awesome tutorial. Thanks!
No worries bro
really the most simple explanation :-) Thank you
pwoli machaan....good explanation broii
Thanks, Oscar, the introduction of a third dimension which squares one of the variables was quite enlightening! My question: You showed classification but how does this relate to regression? I.e. what are the two classes when regressing y on x1?
nice video mate
good crisp and clear explanation .. Hey Oscar could you please upload videos for SVM with some real-time examples specially for 3D space data-set. Thanks
Great video, Oscar!
I'm pretty sure, you'll get more subscribers if you could deliver some nice animation / 3D visualization about these machine learning concept. Because to be able to visualize in your head is the key to understand these concepts of machine learning.
For example, I finally understand about kernel after I watched another video on youtube. However, I would not understand the concept though, if I did not watch your video in the first place. Your video elaborates better concept than that video even though that video illustrates with a nice 3D animation.
Anyway, nice video projects! I hope you'll make more video about these machine learning in the future. Worth than several hours spent in a AI class.
cheers!
Thanks for the video , maybe you can take this further and explain to us how svm works in time series prediction
Cheers, glad I could help 🙌
Plz upload support vector regression too
What's with musk image thumbnail??
Chilling mostly
Elon if someone enjoys ML
@@OscarAlsing agree!!
That's great
Nice Stuff
Thanks!!!!
Great video for the beginners. Hey oscar could you please upload some practical examples of use cases like predicting machine failure with SVM ??
Hi Navish. Thank you! I'll write that on my list of possible future videos.
thank youuuuuuu
The content is helpful but it would be even more helpful if you made it more clear. Like you were looking into something other than your iPad at 10:40. I don't think that's a good practice while explaining. No offense. Just a piece of advice. :)
Thanks for your input Aravind! I'm glad that you're giving me honest feedback
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