Natural Language Processing:Concept along with Case Study

NLP Foundations Through Code

This course introduces natural language processing from the ground up, aimed at learners with no prior NLP background. Rather than staying purely theoretical, it pairs each concept with Python code so you see how the ideas translate into working text-processing pipelines.

What You'll Cover

• Tokenization and stop-word removal
• Stemming
• Different types of vectorizers
• Word Sense Disambiguation (WSD)
• The practical difference between CountVectorizer and hashing in a spam-filter context

Who It's For

Beginners who want a code-first entry point into NLP rather than a purely conceptual overview. The spam-filter case study gives the core text-processing techniques a concrete, applied context to anchor the theory.