Advanced Analytics with PySpark: Patterns for Learning from Data at Scale Using Python and Spark

Author: Akash Tandon

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9789355422804
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    The amount of data being generated today is staggering and growing. Apache Spark has emerged as the de facto tool to analyze big data and is now a critical part of the data science toolbox. Updated for Spark 3.0, this practical guide brings together Spark, statistical methods, and real-world datasets to teach you how to approach analytics problems using PySpark, Spark's Python API, and other best practices in Spark programming.

    Data scientists Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills offer an introduction to the Spark ecosystem, then dive into patterns that apply common techniques-including classification, clustering, collaborative filtering, and anomaly detection, to fields such as genomics, security, and finance. This updated edition also covers NLP and image processing.

    If you have a basic understanding of machine learning and statistics and you program in Python, this book will get you started with large-scale data analysis.

    • Familiarize yourself with Spark's programming model and ecosystem
    • Learn general approaches in data science
    • Examine complete implementations that analyze large public datasets
    • Discover which machine learning tools make sense for particular problems
    • Explore code that can be adapted to many uses
    Books
    Author
    Akash Tandon
    Author 2
    Sandy Ryza
    Author 3
    Uri Laserson
    Author 4
    Sean Owen
    Author 5
    Josh Wills
    Binding
    Paperback
    Condition Type
    New
    Country Origin
    India
    Edition
    First
    Gift Wrap
    N
    Lead time to ship in days (if not in stock)
    ships in 12-15 days
    Leadtime to ship in days (default)
    ships in 1-2 days
    Pages
    236
    Publication Date
    27/06/2022
    Publisher
    Shroff/O'Reilly
    Year
    2022
    Dimensions
    Dimensions (W x H x D)
    7 x 9 x 0.5 inch

    Table of Contents (9789355422804_toc.pdf, 39 Kb) [Download]

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