Curve fitting in Python with curve_fit

[@galaxysplus2011]

Thank you, Sir! This was brilliant. Such a difficult topic so nicely explained. I learned very much by watching this video and going through your example code as well.

[@lktyagi88]

Aamzing job! I have seen so many shallow people delivering heavy concepts but you just nailed everything down to the details..Awsome Job..

[@hsinghal1]

That was brilliant. It was really hsrd to go through the mathematical jargon available on internet. Thank you for nice explanation.

[@ARBB1]

I accidentally ignored this video; *my savior has finally returned*

[@dainisk586]

What an absolute unit. Great cheers to you, mate, you saved my ass big time. Bonzer job on explaining the material better than my profs

[@rafaelem7174]

If I could give you 200k likes I'll do it. I love your simple explanation of the covariance interpretation

[@nkanyisombatha5384]

Very nice video Brant Carlson. You may have forgotten that it is t^2 at 4.o6 min. Thanks a lot for this best class.

[@giovannisucci5624]

Thank you for this lesson Dr. Carlson. Very nice and clear.

[@marextrem1]

Thanks for the Videos, Please keep going, science deserves it !!

[@Chatterjeepal]

THE BOI IS BACK :bless::bless::bless::bless::bless::bless::bless:

[@PatrickBrowne]

Thanks for the video and the code examples ! It was very easy to build upon.

[@PotatoForce42]

This video is awesome. Thank you very much for the detailed explanation

[@XanderGouws]

HE'S BACK BOYS

[@anfilaot]

You saved me, and I wish you had more videos!!!

[@samuelhughes]

You saved me man, thank you so much

[@sjamielm]

Great job and very useful content

[@aneedfortheory]

Hello Brant. Great video! One thing though. Is your formula for the chi-squared statistic correct? I appreciate your detailed explanation of the formula but when I tried to source the formula online, the division of each of the n terms isn't by the uncertainty in the respective terms/contributions but rather the contributions themselves. There is another formula in which the mean is subtracted from each of the data values and then divided by the uncertainty. Is this latter expression the one you were after?

[@AlenvertDiexon]

Hello Brant, thanks for the great video. I also know the formula with ((Observation-Expectation)**2) / Expectation.

[@jeremyblow1603]

See "reduced chi-squared statistic" which uses a weighted sum of squared deviations.

[@tonycardinal413]

Thank you so much for posting this. Ques: If there is a high covariance between the parameters why is this bad? I'm not understanding why this would be bad. thanx!

[@tritruong7867]

PROFESSOR I MISSED YOU :D

[@mclark23]

Excellent. I like the math lesson!!!!!!!!!!!

[@canowow11]

incredible video, thank you very much

[@paulbalduin]

how do I include an uncertainty in both the x and the y value? does curve_fit only work for fits that include only the uncertainty for the y variable?

[@coscinaippogrifo]

Can someone tell me where I can find the library for that interact function called at 13:45, please?

[@arupmarik]

Sir please upload more Videos on physics like old quantum theory..etc

[@oAbraksas]

What if there are errors on both axes?

[@cd8836]

Thank you!

[@000bHd000]

OH SHOOT HE BACK

[@ayanwoyegideon8058]

Great video. I am working on a task that involves curve fitting a curve on another curve (or say data points) and I can't seem to be getting it. The curve I want to fit was generated with a UnivariateSpline of degree 5 and hence don't know how to generate it's mathematical function/representation that I can use with the curve_fit function. I need help please.

[@KarthikeyanMmmm]

hello sir , is there any similar package in python as curve fit , in which we can able to impose some constraints ( like suring regression at a particular point slope should be a specific value) during regression, or is there any posiblity in curve_fit to impose some constraints

[@TheAteris1]

It was a very nice "lecture", would it be possible to get one on the ODR package to fit in python?

[@igoaaronlu8142]

good job thank you

[@maxhansen5166]

very good tutorial. However it would be much better to have the imports on the slides or maybe at least import the packages with aliases. Would make it much more convenient to follow, particularly if you don't have the exact function assignments present.

[@mariohernandez6905]

Thank you very much!

[@XanderGouws]

Would you consider making a video about how the curve_fit() function works?

[@pAulseperformance]

This is exactly what is needed

[@goose_clues]

why don't you just read the *Fine* manual.

[@albasitdanoon7611]

excellent video, thanks. what if we dont have a mathematical function, I have two columns of data, one observed and one expected , how would that look like in python script? Thanks.

[@vanarsamadi]

Plot first your data, and then look for a model that have the shape of the data Plot

[@murilotimo]

Excelente aula, Muito Obrigado.

[@andrzejolczak8924]

What kind of device do you use for handwriting?

[@mclark23]

You know, I've taken may statistical classes (but not in college) and a lot of this is new...

[@saidteacher3331]

Doctor how important for a physics student Masters to know coding?.

[@theojaya7798]

virtually none. i graduated with a physics degree with very little coding skills, i only knew very basic matlab because thats all you need really. But seriously please learn how to code even just the basiscs, help a lot with calculation and projects

[@tritruong7867]

Can we get more advanced topics in QM pls???? thanks professor!

[@ing.nicola1706]

wath do you use for writing on video ?

[@neopalm2050]

you're back?

[@colessa366]

can you please do actual work in python? The theory is good but I didn't understand a thing about how actually code from scratch.

[@harsharajendran41088]

how to put initial conditions for gaussian model

[@b354ramen8]

dear proffosor Hi : we waiting elektromagnetic theory lecture. So ?

[@trouserpython3857]

Thanks bro

[@mclark23]

I made a folder called "Great" and I put the link to this there...

[@r2ei64]

.