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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
Author Profile Icon Rick Hattem
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

Versatile AI libraries and utilities

Python is by far the most popular language when it comes to developing AI systems. The result of this popularity is that there are a huge number of libraries available for every branch of AI you can think of. There is at least a single good library for nearly every AI technique, and often dozens.

In this section of this chapter, you will find a curated (and incomplete) list of useful AI libraries split into segments. There are many more that are not mentioned due to being too specific, too new, or simply because I have omitted them owing to the great number of libraries that are out there.

scikit-learn – Machine learning in Python

The scikit-learn library is an extremely versatile machine learning library that covers many AI topics; for many of them, this should be your starting point. We have already seen the scikit-image library earlier, which is a part of the scikit-learn project, but there are many more options.

The...

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