This course provides an understanding of natural language processing, its tools, techniques, philosophy and principle. It will cover Tokenization, Stop Words and Word Embedding.
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
