Question: This question is from the topic Hidden Markov Models-based Tagging in natural language processing course . i have asked same question earlier, some fake expert

This question is from the topic "Hidden Markov Models-based Tagging" in

This question is from the topic "Hidden Markov Models-based Tagging" in natural language processing course. i have asked same question earlier, some fake expert answered some shit. Donot copy paste the same. Python code is required which should be run in google colab. Do not copy-paste some random code in chatGPT or the internet. Need both code and output screenshots.

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Design a program to tag all the string as shown below and evaluate the emmision probality and transition probability table. Mary Jane can see Will Spot will see Mary Will Jane spot Mary? Mary will pat Spot Also, after the formulation of these table print the emmision probality and transition probability with the probability of this sequence being correct for the string 'Will can spot Mary

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