Natural Language Processing Tutorial in Tamil | Artifical Intelligence Basics (101 Course)

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******************** Natural Language Processing Basics:
Technology which helps to interact between humans and machines with natural language.
Nat­ur­al Lan­guage Pro­cessing is a field that cov­ers com­puter un­der­stand­ing and ma­nip­u­la­tion of hu­man lan­guage, and it’s ripe with pos­sib­il­it­ies for news­gath­er­ing - Anthony Pesce
Applications: Automatic summarization, Translation, Named entity recognition, Relationship extraction, and etc.

Tokenization:
It will segment an input character sequence into tokens.
Tokens can be words, numbers, punctuations, and etc.

Types of Tokenizer:
Whitespace Tokenizer - Non whitespace sequences are identified as tokens
Simple Tokenizer - A character class tokenizer, sequences of the same character class are tokens
Learnable Tokenizer - A maximum entropy tokenizer, detects token boundaries based on probability model

Named Entity Recognizition:
It detect named entities like person, org, place, date, and etc.
It predicts the entities based on model which was trained using the labelled data.
It is a supervised learning.

Document Categorizer:
It can classify text into pre-defined categories.
It is a supervised learning.
We need to train the document categorizer with labelled data.

Parts of Speech:
It distinguishes the tokens into Noun, Adjective, Verb, and etc.
It is a supervised learning.
The most popular tag set is Penn Treebank tagset


For more details & source code check out: https://programmingline.com/2019/02/n...

#naturallanguageprocessing #nlp #programmingline #rakesh #rake

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