Dask: the definitive guide
The exponentially-increasing volume and complexity of data make scalability and reliability increasingly challenging issues. But while modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing, many Python tools weren't designed to leverage this parallelism....
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Sebastopol, CA
O'Reilly Media, Inc.
2023
|
| Ausgabe: | [First edition]. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781098117139/?ar |
| Zusammenfassung: | The exponentially-increasing volume and complexity of data make scalability and reliability increasingly challenging issues. But while modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing, many Python tools weren't designed to leverage this parallelism. Using Dask to parallelize Python workflows delivers a competitive advantage by reducing turn-around time, freeing you to work on more interesting or complex data problems. |
| Beschreibung: | "Early release, raw & unedited." |
| Umfang: | 1 Online-Ressource (78 Seiten) illustrations |
| ISBN: | 9781098117139 1098117131 |
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| indexdate | 2025-04-10T09:36:29Z |
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| isbn | 9781098117139 1098117131 |
| language | English |
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| spelling | Rocklin, Matthew VerfasserIn aut Dask the definitive guide by Matthew Rocklin, Matthew Powers, and Richard Pelgrim [First edition]. Sebastopol, CA O'Reilly Media, Inc. 2023 1 Online-Ressource (78 Seiten) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier "Early release, raw & unedited." The exponentially-increasing volume and complexity of data make scalability and reliability increasingly challenging issues. But while modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing, many Python tools weren't designed to leverage this parallelism. Using Dask to parallelize Python workflows delivers a competitive advantage by reducing turn-around time, freeing you to work on more interesting or complex data problems. Python (Computer program language) Data mining Electronic data processing Distributed processing Information visualization Electronic data processing ; Distributed processing Powers, Matthew VerfasserIn aut Pelgrim, Richard VerfasserIn aut |
| spellingShingle | Rocklin, Matthew Powers, Matthew Pelgrim, Richard Dask the definitive guide Python (Computer program language) Data mining Electronic data processing Distributed processing Information visualization Electronic data processing ; Distributed processing |
| title | Dask the definitive guide |
| title_auth | Dask the definitive guide |
| title_exact_search | Dask the definitive guide |
| title_full | Dask the definitive guide by Matthew Rocklin, Matthew Powers, and Richard Pelgrim |
| title_fullStr | Dask the definitive guide by Matthew Rocklin, Matthew Powers, and Richard Pelgrim |
| title_full_unstemmed | Dask the definitive guide by Matthew Rocklin, Matthew Powers, and Richard Pelgrim |
| title_short | Dask |
| title_sort | dask the definitive guide |
| title_sub | the definitive guide |
| topic | Python (Computer program language) Data mining Electronic data processing Distributed processing Information visualization Electronic data processing ; Distributed processing |
| topic_facet | Python (Computer program language) Data mining Electronic data processing Distributed processing Information visualization Electronic data processing ; Distributed processing |
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