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What is Natural Language Processing (NLP)?

Natural Language Processing (NLP) is a process of manipulating or understanding the text or speech by any software or machine. An analogy is that humans interact and understand each other’s views and respond with the appropriate answer. In NLP, this interaction, understanding, and response are made by a computer instead of a human.

Syllabus of TensorFlow Training

Module 1: NLTK Syllabus

Lesson 1 - Natural Language Processing Tutorial: What is NLP? Examples
Lesson 2 - How to Download & Install NLTK on Windows/Mac
Lesson 3 - NLTK Tokenize: Words and Sentences Tokenizer with Example
Lesson 4 - POS Tagging with NLTK and Chunking in NLP [EXAMPLES]
Lesson 4 - Stemming and Lemmatization with Python NLTK
Lesson 4 - WordNet with NLTK: Finding Synonyms for words in Python
Lesson 4 - Word Embedding Tutorial: word2vec using Gensim [EXAMPLE]
Lesson 4 - Seq2seq (Sequence to Sequence) Model with PyTorch

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29-Dec-2025

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Key Features

40 Hours Course Duration
Industry Expert Faculties
100% Job Oriented Training

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Free Demo Class Available
Completed 500+ Batches
Certification Guidance

Why Learn Natural Language Toolkit?

Learning Natural Language Toolkit will help you add an extra skill and also enhance your knowledge of NLP. Learning NLTK library is also beneficial for professionals to enhance their careers in AI and Natural Language Processing with Python.

What will you learn in this NLTK Tutorial for Beginners?

In this NLTK in Python tutorial, you will learn about introduction to NLTK, how to install NLTK, tokenize words, POS, Tokenization, Stemming, Lemmatization, Punctuation, Character count, word count, WordNet, Word Embedding, seq2seq model, etc.

Get Certified By NLTK & Industry Recognized I.T. Ridge Certificate

All significant economic firms have accredited I.T. Ridge Credential. Following the completion of theoretical and practical workshops, we offer training either to freshmen and corporate trainees alike. The practice of testing application software produced for handheld mobile devices for functionality, usability, and consistency is known as mobile application testing. Tests of mobile applications might be automated or manual.

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