What Does the Gradient Vector Mean Intuitively?

What Does the Gradient Vector Mean Intuitively?

The Math Sorcerer

4 года назад

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Pari Jain
Pari Jain - 15.08.2023 14:48

Kon kon india se hai🙌🙌☺️🇮🇳🇮🇳
👍👍👇👇

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Lauschangreifer
Lauschangreifer - 31.07.2023 17:26

Eureka! Thank you very much!

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Soheil Hosseinzadeh
Soheil Hosseinzadeh - 18.06.2023 19:38

The best explanation I've ever heard, thanks a lot.

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Nomthetho Maseko
Nomthetho Maseko - 30.05.2023 05:42

thank you

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Valentín Molina
Valentín Molina - 12.04.2023 16:36

when did Jeff Bezos grow hair and star explaining calculus??

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Shashank Singh
Shashank Singh - 21.03.2023 09:36

is gradient somewhat like google maps showing directions??

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Tim
Tim - 04.02.2023 16:27

thank you ❤

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wizwilzo aops
wizwilzo aops - 12.12.2022 04:20

thx bro

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Kat Nip
Kat Nip - 08.12.2022 00:52

Thank you!!

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Medaphysics Repository
Medaphysics Repository - 04.12.2022 13:39

Immediately googles “rolling plains” bc I’m so cultured.

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X Epho
X Epho - 29.11.2022 20:57

The best explanation ever on what's gradient vector. Thank you!

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thedrumman64
thedrumman64 - 28.11.2022 00:02

Awesome explanation 🙂

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Varuna
Varuna - 10.10.2022 03:52

Not really. I don't get how a 2D plane gives you a direction to go.

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Fud3
Fud3 - 23.09.2022 07:03

Thank you! Great help for my vector cal / EM review, especially cause it helps me picture what is orthogonal to it!

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A Dalis
A Dalis - 30.08.2022 06:14

It does make sense, but for those who are not familiar with the gradient, they need more graphic illustration. Most students including myself were just told that the gradient is a vector that points in the steepest ascent of any 3-D surface and how to compute it given the surface function, but we were never told or shown what the gradient vector looks like any given point on the surface and whether such vector lies in the 2-D or the 3-D space, and why it points in the direction of the steepest ascent. The easiest example was the paraboloid surface. The steepest ascent on any point on the surface is always in the direction of radial away from the vertex. I think the gradient concept needs more illustration and justification. Any video that is proactive that allows for inputting the function, computes the gradient and graphs the gradient might be a good idea. Thanks.

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ProPea^^
ProPea^^ - 14.07.2022 15:56

But then when we evaluate it at a given point what does the resultant number say? Is it the total increase in magnitude given that we've moved towards that point?

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Naveen Kumar
Naveen Kumar - 08.07.2022 18:33

🥇👏👏👏👏👏👏🥇

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obzen
obzen - 03.04.2022 13:08

fx(f(x,y)) gives the as fast as possible changing x direction and fy(f(x,y)) gives the as fast as possible y direction and vector of these gradient vector am i correct

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MEGA BYTE 01
MEGA BYTE 01 - 11.11.2021 00:45

Ayooo jeeff bezooooozooss is that u ?

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Marco Digi
Marco Digi - 26.04.2020 15:57

Yes I also would like to know the why . And would you mind doing an intuitive version video of directional derivatives using the gradient ? I really want to understand that one as well . Thank you !!

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