This is amazing! our coding professor wants us to do something similar to this, I'm in first year and just finished linear algebra 1, This is a life saver!!!
This is great to hear! Let me point you to the official course website. empossible.net/academics/emp4301_5301/ I recommend using this as your main portal to the course website. It has links to the latest version of the notes and videos as well as other learning resources. Hope this helps!!!
Great video! I wonder just like when we find the polynomial function's parameters as a vector in a matrix form, can we find the fit parameters when our function Gaussian + 1st or 2nd order polynomial function? I am asking because I'd like to use likelihood method to estimate my maximum likelihood parameters in that fit on my gaussian shaped data in the form of histogram. This polynomial represents my background attach to it.
I hope I am understanding your question. The Gaussian function is not linear. The most straightforward way to curve fit to a Gaussian is by nonlinear regression. See the videos for Lectures 5c and 5d here. There is actually an example for a Gaussian function. empossible.net/academics/emp4301_5301/
@@empossible1577 Nope, you haven't get it. I know what you are saying. Actually, I wanna know how to structure the formula of a covariance matrix when you fit univariate Gaussian with random scalar values + 1st or 2nd order polynomial funtion which represent my total function I fit on my data. I am not interested what regression it is. I focus on the covariance matrix structor.
@@empossible1577 I wonder univariate Gaussian + 1st or 2nd order of polynomial function fitting. Can you direct mt to a link to show how to construct the covariance matrix in this spesific case ? Cheers.
@@empossible1577 Do you know anywhere has it? Or, I should ask whether, or not the procedure will differ? All it will change is to total function in the nonlinear regression, not the method, right!
This is amazing! our coding professor wants us to do something similar to this, I'm in first year and just finished linear algebra 1, This is a life saver!!!
This is great to hear! Let me point you to the official course website.
empossible.net/academics/emp4301_5301/
I recommend using this as your main portal to the course website. It has links to the latest version of the notes and videos as well as other learning resources.
Hope this helps!!!
Ngl, matrices make ur life easier. Thx for video, its really help me
Great video! I wonder just like when we find the polynomial function's parameters as a vector in a matrix form, can we find the fit parameters when our function Gaussian + 1st or 2nd order polynomial function? I am asking because I'd like to use likelihood method to estimate my maximum likelihood parameters in that fit on my gaussian shaped data in the form of histogram. This polynomial represents my background attach to it.
I hope I am understanding your question. The Gaussian function is not linear. The most straightforward way to curve fit to a Gaussian is by nonlinear regression. See the videos for Lectures 5c and 5d here. There is actually an example for a Gaussian function.
empossible.net/academics/emp4301_5301/
@@empossible1577 Nope, you haven't get it. I know what you are saying. Actually, I wanna know how to structure the formula of a covariance matrix when you fit univariate Gaussian with random scalar values + 1st or 2nd order polynomial funtion which represent my total function I fit on my data. I am not interested what regression it is. I focus on the covariance matrix structor.
@@empossible1577 I wonder univariate Gaussian + 1st or 2nd order of polynomial function fitting. Can you direct mt to a link to show how to construct the covariance matrix in this spesific case ? Cheers.
@@spyhunter0066 Unfortunately, I do not have any notes on that! Very sorry!!
@@empossible1577 Do you know anywhere has it? Or, I should ask whether, or not the procedure will differ? All it will change is to total function in the nonlinear regression, not the method, right!
Very Informative, Please Make a Video on vectors (Advanced).
What specific topics on vectors are you looking for? Have you looked at Topic 2 here:
empossible.net/academics/emp3302/
Thanks.