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High-Performance Computing with Python 3.x
High-Performance Computing with Python 3.x

High-Performance Computing with Python 3.x: Get to grips with various techniques and tools to provide High-Performance Computing in Python 3.x

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Profile Icon Mohammed Kashif
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€18.99 per month
Video Feb 2019 4hrs 12mins 1st Edition
Video
€120.99
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Free Trial
Renews at €18.99p/m
Arrow left icon
Profile Icon Mohammed Kashif
Arrow right icon
€18.99 per month
Video Feb 2019 4hrs 12mins 1st Edition
Video
€120.99
Subscription
Free Trial
Renews at €18.99p/m
Video
€120.99
Subscription
Free Trial
Renews at €18.99p/m

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Key benefits

  • Master using NumPy, SciPy, and Cython to speed up your numerical computations.
  • Leverage the power of multiprocessing and multithreading in Python for parallelism.
  • Master using Dask to handle large data in a distributed setting and reactive applications in Python.

Description

Python is a versatile programming language. Many industries are now using Python for high-performance computing projects. This course will teach you how to use Python on parallel architectures. You'll learn to use the power of NumPy, SciPy, and Cython to speed up computation. Then you will get to grips with optimizing critical parts of the kernel using various tools. You will also learn how to optimize your programmer using Numba. You'll learn how to perform large-scale computations using Dask and implement distributed applications in Python; finally, you'll construct robust and responsive apps using Reactive programming. By the end, you will have gained a solid knowledge of the most common tools to get you started on HPC with Python. All code files are located on GitHub at this link https://github.com/PacktPublishing/High-Performance-Computing-with-Python-3.x

Who is this book for?

This course will help Python Programmers, Data Analysts and aspiring Data Science professionals familiar with basic Python programming to extend their skillset so as to scale their code and improve their code performance.

What you will learn

  • Use lambda expressions, generators, and iterators to speed up your code.
  • A solid understanding of multiprocessing and multithreading in Python.
  • Optimize performance and efficiency by leveraging NumPy, SciPy, and Cython for numerical computations.
  • Load large data using Dask in a distributed setting.
  • Leverage the power of Numba to make your Python programs run faster.
  • Build reactive applications using Python.

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Feb 28, 2019
Length: 4hrs 12mins
Edition : 1st
Language : English
ISBN-13 : 9781789956252
Category :
Languages :
Tools :

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Free for first 7 days. $19.99 p/m after that. Cancel any time!
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Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : Feb 28, 2019
Length: 4hrs 12mins
Edition : 1st
Language : English
ISBN-13 : 9781789956252
Category :
Languages :
Tools :

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Table of Contents

8 Chapters
Getting Started with Faster and Efficient Python Code Chevron down icon Chevron up icon
Parallel Programming in Python Chevron down icon Chevron up icon
Using NumPy and SciPy to Speedup Computations Chevron down icon Chevron up icon
Optimizing Python Code Using Cython Chevron down icon Chevron up icon
Speeding Up Your Python Code Using Numba Chevron down icon Chevron up icon
Distributed Computing Using Python Chevron down icon Chevron up icon
Distributed Programming Using Dask Chevron down icon Chevron up icon
Reactive Programming Using Python Chevron down icon Chevron up icon
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