Book Image

Hands-On Python Natural Language Processing

By : Aman Kedia, Mayank Rasu
4 (1)
Book Image

Hands-On Python Natural Language Processing

4 (1)
By: Aman Kedia, Mayank Rasu

Overview of this book

Natural Language Processing (NLP) is the subfield in computational linguistics that enables computers to understand, process, and analyze text. This book caters to the unmet demand for hands-on training of NLP concepts and provides exposure to real-world applications along with a solid theoretical grounding. This book starts by introducing you to the field of NLP and its applications, along with the modern Python libraries that you'll use to build your NLP-powered apps. With the help of practical examples, you’ll learn how to build reasonably sophisticated NLP applications, and cover various methodologies and challenges in deploying NLP applications in the real world. You'll cover key NLP tasks such as text classification, semantic embedding, sentiment analysis, machine translation, and developing a chatbot using machine learning and deep learning techniques. The book will also help you discover how machine learning techniques play a vital role in making your linguistic apps smart. Every chapter is accompanied by examples of real-world applications to help you build impressive NLP applications of your own. By the end of this NLP book, you’ll be able to work with language data, use machine learning to identify patterns in text, and get acquainted with the advancements in NLP.
Table of Contents (16 chapters)
1
Section 1: Introduction
4
Section 2: Natural Language Representation and Mathematics
9
Section 3: NLP and Learning

Understanding Python with NLP

Python is a high-level, object-oriented programming language that has experienced a meteoric rise in popularity. It is an open source programming language, meaning anyone with a functioning computer can download and start using Python. Python's syntax is simple and aids in code readability, ease of use in terms of debugging, and supports Python modules, thereby encouraging modularity and scalability.

In addition, it has many other features that contribute to its halo and make it an extremely popular language in the developer community. A prominent drawback often attributed to Python is its relatively slower execution speed compared to compiled languages. However, Python's performance is shown to be comparable to other languages and it can be vastly improved by employing clever programming techniques or using libraries built using compiled languages.

If you are a Python beginner, you may consider downloading the Python Anaconda distribution (https...