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| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Sebastopol, CA
O'Reilly Media
2023
|
| Edition: | First edition. |
| Subjects: | |
| Links: | https://learning.oreilly.com/library/view/-/9781098119867/?ar |
| Summary: | 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. |
| Item Description: | Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on August 18, 2023) |
| Physical Description: | 1 Online-Ressource |
| ISBN: | 9781098119843 1098119843 9781098119836 1098119835 |
Staff View
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| spelling | Karau, Holden VerfasserIn aut Scaling Python with Dask from data science to machine learning Holden Karau & Mika Kimmins First edition. Sebastopol, CA O'Reilly Media 2023 ©2023 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on August 18, 2023) 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. Python (Computer program language) Cloud computing Python (Langage de programmation) Infonuagique Kimmins, Mika VerfasserIn aut 1098119878 Erscheint auch als Druck-Ausgabe 1098119878 |
| spellingShingle | Karau, Holden Kimmins, Mika Scaling Python with Dask from data science to machine learning Python (Computer program language) Cloud computing Python (Langage de programmation) Infonuagique |
| title | Scaling Python with Dask from data science to machine learning |
| title_auth | Scaling Python with Dask from data science to machine learning |
| title_exact_search | Scaling Python with Dask from data science to machine learning |
| title_full | Scaling Python with Dask from data science to machine learning Holden Karau & Mika Kimmins |
| title_fullStr | Scaling Python with Dask from data science to machine learning Holden Karau & Mika Kimmins |
| title_full_unstemmed | Scaling Python with Dask from data science to machine learning Holden Karau & Mika Kimmins |
| title_short | Scaling Python with Dask |
| title_sort | scaling python with dask from data science to machine learning |
| title_sub | from data science to machine learning |
| topic | Python (Computer program language) Cloud computing Python (Langage de programmation) Infonuagique |
| topic_facet | Python (Computer program language) Cloud computing Python (Langage de programmation) Infonuagique |
| work_keys_str_mv | AT karauholden scalingpythonwithdaskfromdatasciencetomachinelearning AT kimminsmika scalingpythonwithdaskfromdatasciencetomachinelearning |