Book Image

Natural Language Processing with Python Quick Start Guide

By : Nirant Kasliwal
Book Image

Natural Language Processing with Python Quick Start Guide

By: Nirant Kasliwal

Overview of this book

NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP. The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a work?ow for building NLP applications. We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn. We conclude by deploying these models as REST APIs with Flask. By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges.
Table of Contents (10 chapters)

Why chatbots as a learning example?

So far, we have built an application for every NLP topic that we have seen:

  • Text cleaning using grammar and vocabulary insights
  • Linguistics (and statistical parsers), to mine questions from text
  • Entity recognition for information extraction
  • Supervised text classification using both machine learning and deep learning
  • Text similarity using text-based vectors such as GloVe/word2vec

We will now combine all of them into a much more complicated setup and write our own chatbot from scratch. But, before you build anything from scratch, you should ask why.

Why build a chatbot?

A related questions is why should we build our own chatbots? Why can't I use FB/MSFT/some other cloud service?