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Data Science at the Command Line: Obtain, Scrub, Explore, and Model Data with UNIX Power Tools, (Paperback)
Learn how to greatly improve your data science workflow by leveraging the command line's power.
Data Science at the Command Line: Obtain, Scrub, Explore, and Model Data with UNIX Power Tools, (Paperback)
Item #: 44876900

Data Science at the Command Line: Obtain, Scrub, Explore, and Model Data with UNIX Power Tools, (Paperback)

Item #: 44876900

AED 184

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    Learn how to greatly improve your data science workflow by leveraging the command line's power.
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    What Stands Out

    Command Line Mastery
    Master data science techniques using powerful UNIX command line tools, enhancing productivity and efficiency for data analysts and scientists looking to streamline their workflow.
    Comprehensive Workflow
    Provides a complete data science workflow from obtaining to modeling data, making it ideal for beginners and seasoned professionals wanting to refine their processes.
    Practical Applications
    Offers hands-on examples and real-world applications, enabling readers to directly apply learned concepts to their data challenges, boosting practical understanding and skills.

    Product Details

    Find, Clean, Analyze & Model Data with Unix Power Tools. Get the paperback edition of Data Science at the Command Line from Ubuy UAE.
    • Learn how to use command-line tools to efficiently obtain, scrub, explore, and model data
    • Access a Docker image containing over 100 Unix power tools for Windows, macOS, or Linux
    • Discover the agility, scalability, and extensibility of the command line technology
    • Improve data science workflow by integrating command-line power with Python or R processing
    • Ideal for data scientists, analysts, engineers, system administrators, and researchers
    • Explore operations such as obtaining data from various sources, data scrubbing, visualization, and modeling
    Book formatPaperback
    Fiction/nonfictionNon-Fiction
    GenreComputing & Internet
    Publication dateSeptember, 2021
    Pages280
    Reading levelProfessional and Scholarly
    SubgenreDatabase Administration & Management
    Series titleNo Series
    Edition2nd Edition
    PublisherO'Reilly Media
    Original languagesEnglish
    LanguageEnglish
    Is collectibleN
    Recording time0 min
    Retail packagingSingle Piece
    Assembled product dimensions (l x w x h)7.00 x 0.59 x 9.19 in (17.8 x 1.5 x 23.3 cm)
    Assembled product weight1 lb (450 grams)
    Bisac subject headingComputers

    Who Should Buy?

    Suitable For
    • Data Enthusiasts

      Individuals eager to enhance their data manipulation skills using command line tools for better efficiency.

    • UNIX Users

      Users familiar with UNIX who want to apply command line techniques to data science tasks effectively.

    • Self-Learners

      Individuals motivated to learn data science independently through practical examples and hands-on exercises.

    Not Suitable For
    • Beginners

      Complete newcomers to data science without UNIX knowledge may struggle to grasp the concepts presented in this book.

    Product Description

    Data Science at the Command Line: Obtain, Scrub, Explore, and Model Data with UNIX Power Tools, (Paperback)

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    Jeroen Janssens All Books Editorial Review

    Data Science at the Command Line: Obtain, Scrub, Explore, and Model Data with UNIX Power Tools, is a non-fiction paperback published by O'Reilly Media in September 2021. This second edition spans 280 pages and is tailored for a professional and scholarly audience, focusing on database administration and management in computing and internet. The book empowers readers with UNIX power tools essential for effectively obtaining, scrubbing, and modeling data. It serves as an indispensable resource for data professionals seeking practical command-line techniques to streamline their workflow.

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    Pros

    • Comprehensive guide for data science workflows
    • Focuses on using UNIX power tools
    • Ideal for professional and scholarly readers
    • Clear instructions for data modeling
    • Practical examples enhance learning

    Cons

    • May not suit casual readers or beginners

    Product Price History

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