NLP_Quickbook

Why we included this project

These notebooks are written for practicing engineers who want to get NLP work done, not for students working through a textbook. The author organizes the material into seven themes and says up front that you can skim, pick the chapter that matches your current problem, and jump in without reading everything before it. Early notebooks cover text cleaning, spell correction, and spaCy-based work like redacting names and generating questions, then move on to word embeddings with gensim and text classification. Later chapters show how to build data loaders, training loops, and a simple intent-based chatbot from scratch, so you see the engineering decisions behind the code rather than just the API calls. If you are starting out with NLP in Python or want a code-first refresher on a specific technique, this is a practical companion to the official documentation.