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. This course is designed for people interested in learning NLP from scratch. No prior knowledge of NLP techniques is assumed.
Course Outcome: –
On completion of this course, the students will be able to
- Understand the concepts of Natural Language Processing (NLP) along with Machine Learning.
- Understand the nature of text data and how to work with it using NLTK.
- Load and manipulate your text data.
- Hands on to code the NLP related project.
- Apply various concepts of NLP in other application areas.
Module 1 – Introduction to NLP and NLTK
About NLP and its Applications
About Natural Language Toolkit
Getting Started with NLTK
Module 2 – Introduction to Basics Python
List, Tuple and Dictionary
Making Decisions and Taking Control
Conditionals, Operating on Every Element, Nested Code Blocks, Looping with Conditions
Module 3 – Operations on Text Data
Searching for Text
Texts as Lists of Word
List, Indexing list, variables, strings
Fine-Grained Selection of Words
Counting Other Things
Module 4 – Using NLTK Corpora for NLP
Accessing Text Corpora and Lexical Resources
Web and Chat Text Corpus
Inaugural Address Corpus
Create and Load your own Corpus
Module 5 – Lexical Resources
Module 6 – Text Data Preprocessing
Stop word removal
Tokenization: Word Tokenization and Sentence Tokenization
Feature Extraction Techniques
Bag of Words: CountVectorizer and TfidfVectorizer
Module 7 – Process Web Text Data
Processing Raw Text
Accessing Text from the Web
Dealing with HTML
Processing RSS Feeds
Reading Local Files
Module 8 – Regular Expressions
Regular Expressions for Detecting Word Patterns
Regular Expressions for Extracting Word Pieces
Regular Expressions for Tokenization
Regular Expressions for Stemming
Module 9 – Machine Learning for NLP
What is Machine Learning?
Types of Machine Learning
Classification Algorithms: Naive Bayes, SVM and KNN
Module 10 – Model Building
Overview of Text Classification
Learning to Classify Text
Deep Learning for NLP
Module 11 – Hands on for NLP based Projects
Sentiment Analysis: Twitter Sentiment Analysis
1.Basic of any programming knowledge.
2.Student should have good logical and reasoning skill
Duration & Timings :
Duration – 30 Hours.
Training Type: Online Live Interactive Session.
Access to Class Recordings.
Weekday Session – Mon – Thu 8:30 PM – 10:30 PM EST– 4 Weeks. July 6, 2020.
Weekend Session – Sat & Sun 9:30 AM to 12:30 PM (EST) – 5 Weeks. July 25, 2020.