Gradients and Partial Derivatives

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Excelent

Best video on internet to understand Gradient!!

Typical highlands ⛰

INCREDIBLE

So So So beautifully Explained... Thank you So much...

Underrated asf!!

шок. 10 из 10. Спасибо огромное!

but how about temperature function T(x,y,z). I can't grasp the visualization of function of 3 variable

Gracias

Good afternoon Fellow mathematicians, could you please help? There is a function of two variables. I need to find its minimum. I start from a certain point. Next, what is the minimum search algorithm? For example: an increment of one variable is taken, a function is considered, we look - less or more than the previous step. Further we take an increment by the same change or another? Or it is necessary to take an increment at once of two variables?

You are actually a chad. Thanks.

Nice visualisation. Nobody can explain this mathematical concept better than you. Thanks for your efforts.❤️❤️

Those who came to visit this video from the recommendation of Aanand sir 😂😂😂 give a like

This video should be shown to all students learning integrals honestly. It is such a useful visualization, which really captures the reality of what the math is meant to model.

India's rote learning has never taught this magical concept that you explained. It's crystal clear.

Most efficent way to explain gradient.Thanks.

a very good explanation

What an easy way to explain a subject that can turn difficult to understand sometimes

I have a really great intuition of this in machine learning topics (gradient descent & optimizing), this is really helpful and makes learning about not only ML but the maths behind it clear!

Amazing

A week's worth of lectures condensed into a 5 minute long enlightenment! We need more videos like this👏👏

What’s the function used in this video? I’m trying to find a surface with lots of “mountains”to animate like this one to make my own animation program

Can you help me to gragh chain rool by 3D.
I need that gragh necessary

Thanks a lot 😊

Never seen such an explanation about this . 😁

this isn't Kira Vincent right?

Nice video. I need a video on Total derivative at a point p(x,y,z,t) for the scalar function f(x,y,z,t). For CFD learning.



Thanks in advance

Thanks

At 'c' the fluid drop (as Bohr would see) must turn around even as its course begins up or down, so that the oscillation keeps the particle stationary.

OMG this video saves me

it is the best way that a teacher may describe a concept

اشكر موسيقى زورو 😂

that is the best math video i have ever seen

Bro keep doing this awsome videos, you are the best !

GENIAAAAAAAAAAAAAAAAAAAAAAA

Thank you so much mam it's really helpful for me who is just entering in the world of physics

Sometimes I wish I could give more likes than one :')

Love you guys, this is the way maths is supposed to be taught.

Love your video 👌

You had created this amazing animation with ultimate dedication....wooow...all are perfect...i give my subscription today...thank you for this valueble video....

Amazing video and animations ! Just a point that I hardly get. When you draw the arrow representing direction of the slope, it naturally points towards direction of the steepest ascent, why ? why not towards the steepest descent ? Is it related to the basis orientation, I mean the direction of the unit vectors of the basis or not at all ? Because if the arrow is just dz/dx and not dz/dx times the basis vector x, I don't see how we can get an arrow/direction, we will just have a coefficient. Am I right or what am I totally missing ? It's been a couple of days that I'm struggling with that... thanks anyway !

Thank you. Great job.It's amazing explanation....can you added the proof of gradient algorithm's mathematical figures like w = w - α.d/dwJ(w,b) where α = alpha, J(w,b) = cost function, d/dw = derivative with respect to w.

At last, à very clear explanation of gradient!

I wish we had such graphics visualisation 20 years Earlier. Teacher worked hard to explain all on black board with chalk .

What does it means that every point has an "arrow" that represent the partial derivative ?

Hungarian Rhapsody 2 in the intro?? Wow

just amazinggg

Thanks,this is d
best explantion available

fascinating