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Very intuitive lecture and made it easier. I am facing issue in using CVX tool in my matlab. Can any one help?

Well done and thank you for thr video. the lecturer is chewing a gum or something else during the lecture. Its disgusting 😮

Thank you for the lecture Can anyone explain the reason behind the other factors apart from the loss function in the optimization equation? why do we need to reduce the distance of the line or the hyperplane center from the axis central point? -> ||w||^2 and what is the 'subject to' condition? how did it come by or what is its purpose? why should the points be parallel to the SVM line ( assuming dot product) correct me on this if it is wrong

Extremely bad English Pronounciation. No one misses the arrogance and bad deliverance of scientific Content. It is not even close to that of Brunton's Excellent Lectures. The Greatest Dislike 👎👎👎

Excellent video:)

Thank you Nathan

Are the PowerPoint slides for this course available anywhere?

Are the PowerPoint slides for this course available anywhere? You said there will be an accompanying website. None is provided in the description.

Are the PowerPoint slides for this course available anywhere?

21:45 Bi-CGSTAB

Nice explanation professor

ty

This guy has always been the f*kn BOSSS!

Critically damped has no oscillations. It is fastest aperiodic

Great Explanation

Love this lecture:)

Multiscale modeling!

Could anyone elaborate on the last comment regarding Monte Carlo simulation around 22:50? If the reduced model does not yield sufficiently accurate qualitative/quantitative predictions, then how would the Monte Carlo simulation give good results?

Please sir how can i implement the backpropagation in the SPSS software

Bit weird, you replace some variables and now it looks like a linear equation, except all the nonlinear stuff has been wiped under the carpet, but is stil there 🤔. I'm in the middle of your lecture, curious how this will work out, of course it will.

This is a great lecture 👌

What is a lot of weights? The problem I have had is that it is hard to find the gradient where the derivative of all the parameters are minimized at once. Usually, there is a parameter or two that will significantly increase the sum of squared errors or mean squared error so the step can't be big and one of the many parameters will keep the parameter set from moving towards a minimum.. In other words, the valley of the data set of parameter is trying to walk down is very narrow. I have lots of real data. GD always has problems with optimizing his data. There are many algorithms that a much better if the number of parameters is less than 25. The professor's visual example is OK for teaching but is too simple.easy,

The linear algebra / functional analysis perspective of representing a function with a new coordinate system of orthogonal sinusoidal basis is where it makes Fourier transform clicks.

It really needs to be a tall combustion so that it has a 100% detonation at the Nozzle

Would the playback speed option on this video be a good example of scaling for an acoustic signal?

Hi Nathan. Thanks for your great lesson. It's just what I need in my subject at university. However, I have a problem. I can't find the python codes for your video on your website. Sincerely, Jim.

What an amazing teacher! Thank you for putting these videos online.

Here is a list of the whole series of videos on Applied Linear Algebra: ruclips.net/p/PLFB8R5rtkrDrcuIyA1vKAr9F1s-aETOJ3&si=dXl6UYEGpti-l1CE

Here is a list of the whole series of videos on Applied Linear Algebra: ruclips.net/p/PLFB8R5rtkrDrcuIyA1vKAr9F1s-aETOJ3&si=dXl6UYEGpti-l1CE

Here is a list of the whole series of videos on Applied Linear Algebra: ruclips.net/p/PLFB8R5rtkrDrcuIyA1vKAr9F1s-aETOJ3&si=dXl6UYEGpti-l1CE

Here is a list of the whole series of videos on Applied Linear Algebra: ruclips.net/p/PLFB8R5rtkrDrcuIyA1vKAr9F1s-aETOJ3&si=dXl6UYEGpti-l1CE

Here is a list of the whole series of videos on Applied Linear Algebra: ruclips.net/p/PLFB8R5rtkrDrcuIyA1vKAr9F1s-aETOJ3&si=dXl6UYEGpti-l1CE

Here is a list of the whole series of videos on Applied Linear Algebra: ruclips.net/p/PLFB8R5rtkrDrcuIyA1vKAr9F1s-aETOJ3&si=dXl6UYEGpti-l1CE

Here is a list of the whole series of videos on Applied Linear Algebra: ruclips.net/p/PLFB8R5rtkrDrcuIyA1vKAr9F1s-aETOJ3&si=dXl6UYEGpti-l1CE

Thanks, Nathan for your very nice channel, as a Ph.D. student, I found you a perfect teacher.

It was amazing, thanks professor🌹

Unimpressed with only 150 seconds of Specific Impulse in vacuum. NERVA from 1966 had 10x that specific impulse in vacuum.

Amazing lecture. A bit confused about the size of the tall vector made by a 4k image at min 6.31 4096*4096*3 ! = 24 mil

Very excellent! Thank you!!

I have dug around in your content as well as your website. I am looking for the nuts and bolts of how to go from A --> Z with Chebyshev. Your content is as close is as I have gotten. Can you direct me if you have the content somewhere? You have it in your video here with asubn and bsubn but it isn't very clear what you are trying to communicate. Please. Thank you!

Excellent! Thank you!

Best Lecture

Good job 👍💯. I have generated wavelets with the theory of trigonometric partition equations we can create wavelets. It is a new mathodoly that I have discovered. I wrote a book about it. ruclips.net/video/p0Zc9onKQ0Q/видео.htmlsi=dX1K0xLtJ2iWSgf5 ruclips.net/video/3Ebvypj577E/видео.htmlsi=zeLyrZc54430eV5b ruclips.net/video/DV1iJV0oa7Y/видео.htmlsi=798Te0vetj90Q7j1

thank you for this series. really helpful

It would be greatly appreciated if you put the literature here, so that we can follow on the manipulated proofs you have gone throughout the Video Thanks for your efforts.

This very cool. Wow. Smart young fellow.

Jersey made this lecture a perfect 31/10

is your pen ok, professor?😉

Nice to see Matthew McConaughey getting excited about signal processing.

thank you, Sir