Nonlinear Least Squares

Finding the line of best fit using the Nonlinear Least Squares method.

Covers a general function, derivation through Taylor Series.

[joseguerrero]

You explanined in 10 min what my proffesor could't in two weeks

[SalehGoodarzian]

Thank you for your detailed explanation of this method. After learning this method, I tried to write a code to do this example that you introduced here. As you rightly mentioned, initial guess is very important, particularly for c2. By looking at the data, we can have an idea of c2, that is related to the period of the cosine curve. If c2 is guessed too low or too high, the algorithm won't converge, it must be close to the true value...Thank you again for your great video. Educational, detailed, and very helpful.

[victory]

Sir, you are amazing! I wonder how you would explain the Gauss-Newton and Levenberg-Marquardt algorithms as well. Thank you!

[morrismbuba]

What a good explanation? Really got the point Prof.

[gththcoc]

thank you man, that was an excellent explanation

[nmana]

Thank you so much! Can you please explain more about Gauss-Newton and Levenberg-Marquardt algorithms?

[matthewjames]

I'm not sure if this is a typo but you write "t" instead of "x" consistently throughout the video.

[GuideEver]

You have y(x) yet x is never in equation on the right side ?

[haniffshazwanss]

hey there. great video. just wondering how many parameters should we put? does it really matter no matter how many parameter we put in?

[elsbbbb]

That was very helpful ; Thankyou very much, , ,

[alb]

Can you do this for a function with 2 variables e.g f(x, y;a, b) and g(x, y;c, d)

[rishabhsangal]

This was really helpful sir. Thank you :-)

[konstantinmetodiev]

How do you make initial guess for the Ci prime vector (3:40)? Do these values affect the solution convergence? Thank you.

[johnyoung]

Nice Aggie Ring! Thanks & Gig em AERO 23'

[samuelkushnir]

isn't this just gradient descent?