Just wanted to say thank you - your derivation was very helpful.

Terrific, from the intuitive graphical explanation at the beginning to the derivation of the formula. Thank you.

This seemed like an easy to understand concept at the beginning but then it got substantially more complicated as you progressed

This was very useful and well explained - many thanks

Amazing! Thank you so much for this!

Thank you so much for making this video. Really shed the light on this one for me!

Thank you for such an intuitive and clear explanation!

Thanks for the very clear explanation!

Thank you! Being a graduate student, I came across this and I had forgotten how this was derived so this video served as a pretty to-the-point explanation and derivation.

Thanks for the clear explanation of Newton-Raphson algorithm!

This is what I was exactly searching for ! Thank You ♥

This is such a cool way to explain it. Thank you for making this video!!

Amazing. Nicely Explained :)

Excellent video, thanks!

Great illustration and explanation. Thank you

Thank you so much, i have been looking for an explanation forever :)

Great video, really helpful

Thanks, very helpful.

Very great explanation, definitely deserve subscribe and like, keep the good work bro

Really Good video! Thanks for making it easy to understand 😁😁

This video helps me a lot in class thank you :)

very helpful thank you

awesome video

Would be nice if you also show a case where the method is very sensitive to the initial guess, an even results in an infinite cycle of iterations that never converges. Just imagine a function F(x) that has a non-zero local minimum or maximum... you can pick an initial guess Xo (near the location of this local min/max) such that the tangent has nearly 0 slope...this tangent will almost be parallel to the x axis....and therefore its extension will definitely intersect the x-axis, but very far away from the initial guess....then you may have had the root close to Xo, but the method got you far away immediately. You can even construct a function F(x) such that there is a first guess Xo that after the first iteration results in another guess X1, and a second iteration takes X1 back to Xo....and the method cycles between these two values...never converging to the actual root. You can then show that even in this case, with initial guesses that end up in an infinite cycle...you can still re-try with a new guess....the average of all the X's in the cycle....and eventually the root will be found.

This video was better at conveying the message better than 3b1b in respect to manim lol

Great❤

Thanks good video

Awesome

this is dope

🙏 thanks

Please create a video on how to create Mandelbrot set which is at the end of this video.

If your calculator has a CALC function you can set up the expression, enter the starting value, hit =, then, using that answer, just hit CALC again, = ,CALC, =, and so on, iterating as long as you please, and Presto!, the root is solved.

the initial value instead of writing it as x0, can i write my initial value as x1?

👏👏👏👏👏👏👏👏

i signed up for a way to get both roots of an answer, i was greeted by calculus

Looks very similar to 3blue1brown

I actually was messing around in the graphic calculator and invented the f'(p)(x-p) + f(p), p being the x of a given point. Ah math.

Hi I accidentally discovered a formula for finding matrix calculus and I named it the khalam Newton method the method takes the derivative of determinant and it converges very fast I thought it's an discovery if you are intrested we can talk about that