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Scaling Python with Dask - by Holden Karau & Mika Kimmins (Paperback)

Name: Scaling Python with Dask - by Holden Karau & Mika Kimmins (Paperback)
Brand: O'Reilly Media
SKU: 1010455088
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Highlights

Modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing.
Author(s): Holden Karau & Mika Kimmins
223 Pages
Computers + Internet,

Description

About the Book

Modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing. But many scientific Python tools were not designed to leverage this parallelism. With this short but thorough resource, data scientists and Python programmers will learn how the Dask open source library for parallel computing provides APIs that make it easy to parallelize PyData libraries including NumPy, pandas, and scikit-learn. Authors Holden Karau and Mika Kimmins show you how to use Dask computations in local systems and then scale to the cloud for heavier workloads. This practical book explains why Dask is popular among industry experts and academics and is used by organizations that include Walmart, Capital One, Harvard Medical School, and NASA. With this book, you'll learn: What Dask is, where you can use it, and how it compares with other tools How to use Dask for batch data parallel processing Key distributed system concepts for working with Dask Methods for using Dask with higher-level APIs and building blocks How to work with integrated libraries such as scikit-learn, pandas, and PyTorch How to use Dask with GPUs.

Book Synopsis

Authors Holden Karau and Mika Kimmins show you how to use Dask computations in local systems and then scale to the cloud for heavier workloads. This practical book explains why Dask is popular among industry experts and academics and is used by organizations that include Walmart, Capital One, Harvard Medical School, and NASA.

With this book, you'll learn:

What Dask is, where you can use it, and how it compares with other tools
How to use Dask for batch data parallel processing
Key distributed system concepts for working with Dask
Methods for using Dask with higher-level APIs and building blocks
How to work with integrated libraries such as scikit-learn, pandas, and PyTorch
How to use Dask with GPUs

Specifications

Dimensions (Overall): 9.19 Inches (H) x 7.0 Inches (W) x .48 Inches (D)

Weight: .81 Pounds

Suggested Age: 22 Years and Up

Number of Pages: 223

Genre: Computers + Internet

Publisher: O'Reilly Media

Format: Paperback

Author: Holden Karau & Mika Kimmins

Language: English

Street Date: August 22, 2023

TCIN: 1010455088

UPC: 9781098119874

Item Number (DPCI): 247-15-2121

Origin: Made in the USA or Imported

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Estimated ship dimensions: 0.48 inches length x 7 inches width x 9.19 inches height

Estimated ship weight: 0.81 pounds

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