Natural Language Toolkit (NLTK) Training in Thimphu, Bhutan

This course provides a comprehensive introduction to Natural Language Toolkit (NLTK), a powerful library for Natural Language Processing (NLP) in Python. Participants will learn text processing, tokenization, stemming, lemmatization, Named Entity Recognition (NER), and sentiment analysis using NLTK.

Introduction to NLTK and Text Preprocessing

• Overview of Natural Language Processing (NLP)
• Setting up NLTK and downloading corpora
• Tokenization: Word and sentence tokenization
• Text normalization: Stemming and Lemmatization
• Stopword removal and text cleaning techniques

Part-of-Speech Tagging, Named Entity Recognition, and Word Frequency Analysis

• Understanding Part-of-Speech (POS) tagging
• Named Entity Recognition (NER) using NLTK's chunking
• Frequency distribution and n-gram models
• Word embeddings: TF-IDF, Word2Vec basics

Sentiment Analysis, Text Classification, and NLP Model Building

• Introduction to sentiment analysis techniques
• Training a text classification model using NLTK
• Building an NLP pipeline for spam detection
• Integration of NLTK with Scikit-Learn for machine learning models
• Hands-on: Developing and deploying a sentiment analysis model