Maximum likelihood estimation (MLE) / Parameter estimation of Bernoulli / KTU Machine learning

#mle #parameterestimation #machinelearning
mle or maximum likelihood estimation is a method to estimate the parameter of a statistical model by maximizing the likelihood function. This tutorial describes in detail what is a likelihood function, mle method and the parameter estimation of bernoulli distribution.
How to find the ml estimate of bernoulli distribution.
Notes
drive.google.c...

[@techsavy5669]

Video seems good, but the non-english-language in between killed it! By any chance, can you re-upload it with in all English. Thanks.

[@Abhishek_mishra1]

Thanks but i have some problem in mid of video u explain in regional language .. i am not able to understand. but hm smj gye thanks

[@smithaengoor7917]

Very simple and effective explanation.

[@jerrysamjames4928]

Hi, Kindly share a video for MLE for Binomial and Gaussian. Bernoulli was very helpful. In different videos its showing different types of derivation. I would like to follow this channel.

[@humble_man30]

couldnt understand the andale pandalam part in between..otherwise good

[@Vaishnavu_minaloor]

Video seems well understanding ! .. Thanks

[@niteshtripathi3673]

Thanks Asha Ji.

[@eduflairktucs7636]

Welcome😊

[@Recreationalhuman]

Ivde malayalam mathi🔥,

[@piyalikarmakar5979]

Ma'am how can I comoute the loss from these? Is the log likelihood value be the loss?

[@muratolisunuh2441]

maam liklihood is the product of probability distribution but in your case you use addition
is it same thing? ma'am can you please reply and say a little more about this

[@dontknow008]

yes it is the product of distribution..but she took the logarithm of likelihood function which is known as log likelihood function. When you take the log of the terms that are multiplied, it converts them into summation. log(a.b) = log a + log b. It is done because log likelihood is easy to differentiate. (Our target is to choose a value for the parameter that maximizes the likelihood function or the log likelihood, coz taking the log doesn't change the nature of the function)

[@ramanathanchockalingam4692]

how to calculate coefficient for feature x1 and x2. Also can you example to calculate coefficient for feature x1,x2..xn in bernouli distribution

[@Shri_Krishna_quotes_1188]

Very nice

[@rajdoc2716]

Semmaiya dilli kodukiringA. Other statistical analysis subject upload pannalaya??

[@Phoenix-wr6rn]

Thankyou mam😇

[@apoorva3635]

What is the parameter that we are maximizing here? Intercept/slope?

[@footballinshorts2711]

We are maximising the probability function

[@thasnisharif7949]

Hello pls can u send me the link of regression and density function topic of this module

[@eduflairktucs7636]

Sorry.. Not all the topics covered

[@AK-cy3ql]

please use pure english

[@positivity798]

Hi... what is your name... you belong to which department...

[@eduflairktucs7636]

Hi I m asha belong to CS dept.

[@positivity798]

@@eduflairktucs7636 ohh ok mam. Please to meet you. Mam will you take class for ME computer science and engineering.

[@eduflairktucs7636]

Not now ...first I have to complete this subject..

[@positivity798]

@@eduflairktucs7636 ohh ok... because I am an BE computer science and engineering graduate and I am moving to ME computer science and engineering that's why I asked you. And I am from Anna University affliated college.

[@all-aroundas8904]

Atleast make videos in English,please

[@be_happy7830]

Ye kia bol rahi h kuch samjh nahi a rahi pure urdu bol na kia fazool bakwas lagi hui h baha eahi h tu😒

[@msrashikaaa5962]

V nice 👍