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Text Data Analytics with NLTK and PYTHON

$400.00 $300.00

Description

About NLTK: –

The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language.

Course Description: –

This course introduces Natural Language Processing (NLP) with the use of Natural Language Tool Kit (NLTK) and Python. Through practical approach, you will get hands-on experience with Natural language concepts and computational linguistics concepts.

Course Outcome: –

On completion of this course, the students will be able to

1.Understand the basic concepts of Natural Language Processing (NLP).

2.Understand how to use the Natural Language Tool Kit.

3.Work with text data using the Natural Language Tool Kit.

4.Load and manipulate your text data.

5.Perform syntax and semantics in natural language processing.

6.Ability to design and analyse various NLP algorithms.

7.Apply various concepts of NLP in other application areas.

Module 1

Introduction to Natural Language Processing
About Natural Language Toolkit
Getting Started with NLTK
NLTK installation
Loading Book

Module 2

Searching Text
Counting Vocabulary
Texts as Lists of Word
List, Indexing list, variables, strings

Module 3

Frequency Distributions
Fine-Grained Selection of Words
Collocations
Counting Other Things

Module 4

Making Decisions and Taking Control
Conditionals, Operating on Every Element, Nested Code Blocks, Looping with Conditions

Module 5

Accessing Text Corpora and Lexical Resources
Gutenberg Corpus
Gutenberg Corpus
Web and Chat Text Corpus
Brown Corpus
Reuters Corpus
Inaugural Address Corpus
Loading your own Corpus

Module 6

Lexical Resources
Wordlist Corpora
Stopword
Name Corpus
Comparative Wordlists
WordNet

Module 7

Processing Raw Text
Accessing Text from the Web
Tokenization
Dealing with HTML
Processing RSS Feeds
Reading Local Files

Module 8

Finding Word Stems
Stemmers
Lemmatization
Segmentation: Sentence Segmentation and Word Segmentation
Writing Results to a File
Text Wrapping

Module 9

Learning to Classify Text
Supervised Classification
Case Study 1: Gender Identification
Case Study 2: Document Classification
Part-of-Speech Tagging

Prerequisites: –

1. Basic of any programming knowledge but Python is preferred.

2. Student should have good logical and reasoning skill

Duration & Timings :

Duration – 25 Hours.

Training Type: Online Live Interactive Session.

Faculty: Experienced.

Access to Class Recordings.

Weekend Session – Sat & Sun 9:30 AM to 12:30 PM (EST) – 5 Weeks. December 14, 2019.

Weekday  Session –  Mon – Thu 8:30 PM – 10:30 PM EST– 4 Weeks. January 6, 2020.

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USA: +1 734 418 2465 | India: +91 40 4018 1306

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