Скачать или смотреть (Lec-65) Natural Language Processing (NLP) | AI বাংলা টিউটোরিয়াল

Welcome to this lecture on Natural Language Processing (NLP)! 🗣️💻
In this video, we dive into how computers understand, interpret, and generate human language. NLP is at the heart of technologies like chatbots, translation services, and AI assistants!

👉 Topics Covered:

What is Natural Language Processing?

Key tasks: Tokenization, Parsing, Sentiment Analysis, and more

Applications of NLP in the real world

Challenges and future directions

Whether you're studying Artificial Intelligence, Machine Learning, or just curious about how machines understand us, this session is for you!

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Natural Language Processing (NLP) refers to AI method of communicating with an intelligent systems using a natural language such as English.

Processing of Natural Language is required when you want an intelligent system like robot to perform as per your instructions, when you want to hear decision from a dialogue based clinical expert system, etc.

The field of NLP involves making computers to perform useful tasks with the natural languages humans use. The input and output of an NLP system can be −

Speech
Written Text
Components of NLP
There are two components of NLP as given −

Natural Language Understanding (NLU)
Understanding involves the following tasks −

Mapping the given input in natural language into useful representations.
Analyzing different aspects of the language.
Natural Language Generation (NLG)
It is the process of producing meaningful phrases and sentences in the form of natural language from some internal representation.

It involves −

Text planning − It includes retrieving the relevant content from knowledge base.

Sentence planning − It includes choosing required words, forming meaningful phrases, setting tone of the sentence.

Text Realization − It is mapping sentence plan into sentence structure.

The NLU is harder than NLG.

Difficulties in NLU
NL has an extremely rich form and structure.

It is very ambiguous. There can be different levels of ambiguity −

Lexical ambiguity − It is at very primitive level such as word-level.

For example, treating the word “board” as noun or verb?

Syntax Level ambiguity − A sentence can be parsed in different ways.

For example, “He lifted the beetle with red cap.” − Did he use cap to lift the beetle or he lifted a beetle that had red cap?

Referential ambiguity − Referring to something using pronouns. For example, Rima went to Gauri. She said, “I am tired.” − Exactly who is tired?

One input can mean different meanings.

Many inputs can mean the same thing.