Description: Scaling Python With Dask : From Data Science to Machine Learning, Paperback by Karau, Holden; Kimmins, Mika, ISBN 1098119878, ISBN-13 9781098119874, Brand New, Free shipping in the US Modern systems contain multicore 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 toolsHow to use Dask for batch data parallel processingKey distributed system concepts for working with DaskMethods for using Dask with higher-level APIs and building blocksHow to work with integrated libraries such as scikit-learn, pandas, and PyTorchHow to use Dask with GPUs
Price: 58.77 USD
Location: Jessup, Maryland
End Time: 2024-09-04T00:15:19.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 14 Days
Refund will be given as: Money Back
Book Title: Scaling Python With Dask : From Data Science to Machine Learning
Number of Pages: 200 Pages
Language: English
Publication Name: Scaling Python with Dask : from Data Science to Machine Learning
Publisher: O'reilly Media, Incorporated
Publication Year: 2023
Item Height: 0.7 in
Subject: Data Modeling & Design, Programming / Open Source, Data Processing, Programming Languages / Python
Item Weight: 13.1 Oz
Type: Textbook
Subject Area: Computers
Item Length: 9.1 in
Author: Mika Kimmins, Holden Karau
Item Width: 7 in
Format: Trade Paperback
