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Advanced Python Programming. Accelerate your Python programs using proven techniques and design patterns - Second Edition

Język publikacji: 1
Autor:
Quan Nguyen
Advanced Python Programming. Accelerate your Python programs using proven techniques and design patterns - Second Edition Quan Nguyen - okladka książki

Advanced Python Programming. Accelerate your Python programs using proven techniques and design patterns - Second Edition Quan Nguyen - okladka książki

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
606
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Python's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages.
In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level.
This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models.
The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming.
You'll also understand the common problems that cause undesirable behavior in concurrent programs.
Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable.
By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.

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O autorze książki

Quan Nguyen is a Python programmer and machine learning enthusiast. He is interested in solving decision-making problems under uncertainty. Quan has authored several books on Python programming and scientific computing. He is currently pursuing a Ph.D. degree in computer science at Washington University in St. Louis, researching Bayesian methods in machine learning.

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