This course provides an understanding of natural language processing, its tools, techniques, philosophy and principle. It will cover Tokenization, Stop Words and Word Embedding.
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Overview
Syllabus
Natural Language Processing for Building AI based Applications | Use Cases(NLP in AI).
Word and Sentence Tokenization Explained | NLP Concepts for Building AI Applications.
Stop Words Explained in Natural Language Processing | NLP Concepts for Building AI Applications.
Word Stemming Explained in Natural Language Processing | NLP Concepts for Building AI Applications.
Lemmatization Explained in Natural Language Processing | NLP Concepts for Building AI Applications.
Word Embedding Introduction for Sentiment Analysis LSTM Model | Contextual Grouping of Words.
How to Build a Word2Vec model for Word Embedding - Part 1 | Gensim library to Train Word2Vec Model.
Generate Word Embedding using Word2Vec & Gensim - Part 2 | See the Magic of Word2Vec in Action.
Taught by
The AI University