Maximum Likelihood Estimator

Maximum Likelihood Estimator:

We use DATA to find Probability and Probability to predict(future) DATA.
Data => Prob
Prob => Data

Take the case of tossing a coin. Lets try to predict best probability(of head) for following data

DATA :    1 0 1 0 1
1 refers to Head, 0 refers to Tails
Prob = 3/5 = .66

_https://youtu.be/VBgqM7GDVfM

Laplacian Estimator:

In cases like with Data as [1] or [1,1,1], our data is n0t good for P(head). So we add fake data to make it bring close to .5, just as it expected for a coin.

_https://youtu.be/wuQodjHyji0

So when we have less data, it is good to have some fake data to put our stats in control to give us better results. Below is the summary video.

_https://youtu.be/oyJwUYRvssg

https://classroom.udacity.com/courses/st101/lessons/48727700/concepts/487122970923

 

 

 

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