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Mastering Python 2E

You're reading from   Mastering Python 2E Write powerful and efficient code using the full range of Python's capabilities

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Product type Paperback
Published in May 2022
Last Updated in May 2022
Publisher Packt
ISBN-13 9781800207721
Length 710 pages
Edition 2nd Edition
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Author (1):
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Rick Hattem Rick Hattem
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Rick Hattem
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Table of Contents (21) Chapters Close

Preface 1. Getting Started – One Environment per Project FREE CHAPTER 2. Interactive Python Interpreters 3. Pythonic Syntax and Common Pitfalls 4. Pythonic Design Patterns 5. Functional Programming – Readability Versus Brevity 6. Decorators – Enabling Code Reuse by Decorating 7. Generators and Coroutines – Infinity, One Step at a Time 8. Metaclasses – Making Classes (Not Instances) Smarter 9. Documentation – How to Use Sphinx and reStructuredText 10. Testing and Logging – Preparing for Bugs 11. Debugging – Solving the Bugs 12. Performance – Tracking and Reducing Your Memory and CPU Usage 13. asyncio – Multithreading without Threads 14. Multiprocessing – When a Single CPU Core Is Not Enough 15. Scientific Python and Plotting 16. Artificial Intelligence 17. Extensions in C/C++, System Calls, and C/C++ Libraries 18. Packaging – Creating Your Own Libraries or Applications 19. Other Books You May Enjoy
20. Index

Natural language processing

NLP is the process of parsing text and understanding its meaning. This can be used to extract knowledge from pieces of text, understand the differences between texts, and more.

There are several well-developed libraries available for this purpose that work quite well. Additionally, there are also hosted pre-trained networks available such as the GPT-3 network, which can be accessed through the OpenAI API.

This network can generate text of such high quality that it is often indistinguishable from human-generated text.

NLTK – Natural Language Toolkit

NLTK is not really a machine learning library by itself like most of the other libraries here, but it’s the basis for many natural language processing libraries. The NLTK project started in 2001 with the purpose of understanding natural languages, and definitely deserves a place in this list.

The project comes bundled with a large collection of corpora and pre-trained models...

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