Code: USD75OFF
This is the code repository for Natural Language Understanding with Python, published by Packt.
Combine natural language technology, deep learning, and large language models to create human-like comprehension
Natural Language Understanding facilitates the organization and structuring of language allowing computer systems to effectively process textual information for various practical applications. Natural Language Understanding with Python will help you explore practical techniques for harnessing NLU to create diverse applications.
Complete with step-by-step explanations of essential concepts and practical examples, you’ll begin by learning about NLU and its applications. You’ll then explore a wide range of current NLU techniques and their most appropriate use-case. In the process, you’ll be introduced to the most useful Python NLU libraries. Not only will you learn the basics of NLU, you’ll also discover practical issues such as acquiring data, evaluating systems, and deploying NLU applications along with their solutions. The book is a comprehensive guide that’ll help you explore techniques and resources that can be used for different applications in the future.
By the end of this book, you’ll be well-versed with the concepts of natural language understanding, deep learning, and large language models (LLMs) for building various AI-based applications.
This book covers the following exciting features:
- Explore the uses and applications of different NLP techniques
- Understand practical data acquisition and system evaluation workflows
- Build cutting-edge and practical NLP applications to solve problems
- Master NLP development from selecting an application to deployment
- Optimize NLP application maintenance after deployment
- Build a strong foundation in neural networks and deep learning for NLU
If you feel this book is for you, get your copy today!
All of the code is organized into folders.
The code will look like the following:
import boto3
import awswrangler as wr
from urllib.parse import unquote_plus
Following is what you need for this book: This book is for python developers, computational linguists, linguists, data scientists, NLP developers, conversational AI developers, and students looking to learn about natural language understanding (NLU) and applying natural language processing (NLP) technology to real problems. Anyone interested in addressing natural language problems will find this book useful. Working knowledge in Python is a must.
With the following software and hardware list you can run all code files present in the book (Chapter 1-16).
| Chapter | Software required | OS required |
|---|---|---|
| 1-15 | Python 3.9 | Any OS |
| 1-15 | pip | Any OS |
| 1-15 | Jupyter Notebooks | Any OS |
| 1-15 | NLTK | Any OS |
| 1-15 | spaCy and displaCy | Any OS |
| 1-15 | Keras | Any OS |
| 1-15 | TensorFlow | Any OS |
| 1-15 | Scikit-learn | Any OS |
| 1-15 | Matplotlib | Any OS |
| 1-15 | Seaborn | Any OS |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Deborah A. Dahl is the principal at Conversational Technologies, with over 30 years of experience in natural language understanding technology. She has developed numerous natural language processing systems for research, commercial, and government applications, including a system for NASA, and speech and natural language components on Android. She has taught over 20 workshops on natural language processing, consulted on many natural language processing applications for her customers, and written over 75 technical papers. Th is is Deborah’s fourth book on natural language understanding topics. Deborah has a PhD in linguistics from the University of Minnesota and postdoctoral studies in cognitive science from the University of Pennsylvania.