Bayesian Parameter Estimation in NLP | Probabilistic Models & Statistical Learning Explained

Описание: Bayesian Parameter Estimation plays a key role in Natural Language Processing (NLP) by helping models learn from data using probability and prior knowledge.
It combines Bayes’ Theorem with statistical learning to estimate parameters in language models like Naive Bayes, HMMs, and topic models.

In this video, you’ll learn:

What is Bayesian Parameter Estimation?

How it’s applied in NLP and Machine Learning

Concepts of prior, likelihood, and posterior

Real-world examples in text classification, speech recognition, and language modeling


Understand how Bayesian methods make NLP models smarter, more adaptive, and data-efficient!


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