NLTK Full Course: Natural Language Processing with Python
🚀 Welcome to the Complete NLTK Full Course!
If you're starting your journey into Natural Language Processing (NLP) using Python, this is the ultimate video for you! In this full course, we dive deep into the Natural Language Toolkit (NLTK) — one of the most widely used Python libraries for NLP.
Whether you're a beginner or looking to sharpen your skills, this tutorial covers everything you need to build real-world NLP applications using NLTK.
📚 What You'll Learn in This Course
✅ Introduction to NLTK and NLP
✅ Installing and Setting Up NLTK
✅ Tokenization (Word, Sentence)
✅ Stopword Removal
✅ Stemming (Porter, Lancaster)
✅ Lemmatization
✅ Part of Speech (POS) Tagging
✅ Named Entity Recognition (NER)
✅ Chunking and Chinking
✅ Text Classification Basics
✅ Frequency Distribution and WordClouds
✅ N-Grams and Collocations
✅ Text Preprocessing Techniques
✅ Parsing and Syntax Trees
✅ Working with Corpora and Lexicons (like WordNet)
✅ Building a Simple NLP Pipeline
✅ Exporting Clean Text for ML Models
💻 Tools & Technologies
Python 3.x
NLTK Library
Jupyter Notebook / Colab
WordCloud & Matplotlib for Visualization
📢 Don’t Forget To:
👍 Like
💬 Comment your questions
🔔 Subscribe for more NLP & AI tutorials
📢 Share this with your friends
🚀 Welcome to the Complete NLTK Full Course!
If you’re starting your journey into Natural Language Processing (NLP) using Python, this is the ultimate video for you! In this full course, we dive deep into the Natural Language Toolkit (NLTK) — one of the most widely used Python libraries for NLP.
Whether you’re a beginner or looking to sharpen your skills, this tutorial covers everything you need to build real-world NLP applications using NLTK.
📚 What You’ll Learn in This Course
✅ Introduction to NLTK and NLP
✅ Installing and Setting Up NLTK
✅ Tokenization (Word, Sentence)
✅ Stopword Removal
✅ Stemming (Porter, Lancaster)
✅ Lemmatization
✅ Part of Speech (POS) Tagging
✅ Named Entity Recognition (NER)
✅ Chunking and Chinking
✅ Text Classification Basics
✅ Frequency Distribution and WordClouds
✅ N-Grams and Collocations
✅ Text Preprocessing Techniques
✅ Parsing and Syntax Trees
✅ Working with Corpora and Lexicons (like WordNet)
✅ Building a Simple NLP Pipeline
✅ Exporting Clean Text for ML Models
💻 Tools & Technologies
Python 3.x
NLTK Library
Jupyter Notebook / Colab
WordCloud & Matplotlib for Visualization
📢 Don’t Forget To:
👍 Like
💬 Comment your questions
🔔 Subscribe for more NLP & AI tutorials
📢 Share this with your friends
