Mastering NLTK for Natural Language Processing

Date Created
22/11/2024

This course provides a comprehensive journey through NLTK, from basics to advanced topics. Learn tokenization, stemming, lemmatization, parsing, sentiment analysis, and more. Build text classification models, explore WordNet, and master advanced language modeling. Ideal for anyone aspiring to excel in natural language processing with Python.

What you will learn -

Introduction to Natural Language Toolkit (NLTK) in Python
Getting Started with NLTK
Understanding Tokenization Techniques in NLTK
Stopwords Removal in Text Processing with Python
Stemming with Porter and Lancaster Stemmer in Python
Lemmatization in Python Using WordNet Lemmatizer
Exploring Parts of Speech Tagging with NLTK in Python
Named Entity Recognition with NLTK in Python
Text Classification Using NLTK in Python
Building a Bag of Words Model in Python for Natural Language Processing
N-Gram Models for Text Analysis in Python
Using WordNet for Synonyms and Antonyms in Python
Chunking with Regular Expressions in NLTK
Parsing Syntax Trees with NLTK
Sentiment Analysis with NLTK
Unlocking Insights with Topic Modeling Using NLTK in Python
Understanding Word Similarity and Distance Metrics in NLTK
Training and Testing Models with NLTK
Building a Custom Corpus with NLTK
Advanced Language Modeling Using NLTK