| Document Type
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BL
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| Record Number
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854627
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| Main Entry
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Daniel, Jesse C.
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| Title & Author
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Data science with Python and Dask /\ Jesse C. Daniel.
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| Publication Statement
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Shelter Island, NY :: Manning Publications,, [2019]
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, ©2019
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| Page. NO
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1 online resource :: illustrations
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| ISBN
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1617295604
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: 9781617295607
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Part 1. The building blocks of scalable computing. Why scalable computing matters -- Introducing Dask -- Part 2. Working with structured data using Dask DataFrames. Introducing Dask DataFrames -- Loading data into DataFrames -- Cleaning and transforming DataFrames -- Summarizing and analyzing DataFrames -- Visualizing DataFrames with Seaborn -- Visualizing location data with Datashader -- Part 3. Extending and deploying Dask. Working with bags and arrays -- Machine learning with Dask-ML -- Scaling and deploying Dask.
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| Abstract
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Data Science with Python and Dask teaches you to build scalable projects that can handle massive datasets. After meeting the Dask framework, you'll analyze data in the NYC Parking Ticket database and use DataFrames to streamline your process. Then, you'll create machine learning models using Dask-ML, build interactive visualizations, and build clusters using AWS and Docker.
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| Subject
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Data mining.
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| Subject
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Electronic data processing-- Distributed processing.
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Information visualization.
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| Subject
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Python (Computer program language)
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Data mining.
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Electronic data processing-- Distributed processing.
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Information visualization.
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| Subject
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Python (Computer program language)
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| Dewey Classification
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004
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| LC Classification
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QA76.73.P98
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