Newton's Method and Optimization - Math Modelling | Lecture 4

In the previous lecture we saw that single variable optimization mostly comes down to finding critical points. That is, finding when the derivative of a function is equal to zero. In practice this can be a difficult process with no way of explicitly getting these roots. In this lecture we review Newton's method for finding roots of functions and show how it can help us to solve optimization problems and perform sensitivity analysis.
For a full analytical introduction to Newton's method, see: • Newton's Method - Real...
This course is taught by Jason Bramburger for Concordia University.
More information on the instructor: hybrid.concord...
Follow @jbramburger7 on Twitter for updates.

[@ryanstrasser4728]

Very Helpful, Thank you.

[@hafsanidhi9269]

Can I know which book(s) are you using as reference?

[@jasonbramburger]

I put together the notes from a number of different sources, but a main contributor is this textbook: shop.elsevier.com/books/mathematical-modeling/meerschaert/978-0-12-386912-8

[@hafsanidhi9269]

@@jasonbramburger Oh, thank you very much professor. Your videos are really helpful and easy to understand, appreciate it a lot.

[@camerashysd7165]

You know Professor Brunton?

[@jasonbramburger]

Yes, I do. I worked with him for a year.