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    Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning

    (ebook) (audiobook) (audiobook) Język publikacji: angielski
    Autorzy:
    Ivan Marin, Ankit Shukla, Sarang VK
    Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning Ivan Marin, Ankit Shukla, Sarang VK - okładka ebooka

    Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning Ivan Marin, Ankit Shukla, Sarang VK - okładka ebooka

    Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning Ivan Marin, Ankit Shukla, Sarang VK - okładka audiobooka MP3

    Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning Ivan Marin, Ankit Shukla, Sarang VK - okładka audiobooks CD

    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    276
    Dostępne formaty:
    PDF
    ePub
    Mobi
    +94 pkt

    Ebook

    94,99 zł

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    Do przechowalni

    Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. With this book, you'll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems.

    The book begins with an introduction to data manipulation in Python using pandas. You'll then get familiar with statistical analysis and plotting techniques. With multiple hands-on activities in store, you'll be able to analyze data that is distributed on several computers by using Dask. As you progress, you'll study how to aggregate data for plots when the entire data cannot be accommodated in memory. You'll also explore Hadoop (HDFS and YARN), which will help you tackle larger datasets. The book also covers Spark and explains how it interacts with other tools.

    By the end of this book, you'll be able to bootstrap your own Python environment, process large files, and manipulate data to generate statistics, metrics, and graphs.

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    O autorach ebooka

    Ivan Marin is a systems architect and data scientist working at Daitan Group, a Campinas-based software company. He designs big data systems for large volumes of data and implements machine learning pipelines end to end using Python and Spark. He is also an active organizer of data science, machine learning, and Python in So Paulo, and has given Python for data science courses at university level.
    Ankit Shukla is a data scientist working with World Wide Technology, a leading US-based technology solution provider, where he develops and deploys machine learning and artificial intelligence solutions to solve business problems and create actual dollar value for clients. He is also part of the company's R&D initiative, which is responsible for producing intellectual property, building capabilities in new areas, and publishing cutting-edge research in corporate white papers. Besides tinkering with AI/ML models, he likes to read and is a big-time foodie.
    Sarang VK is a lead data scientist at StraitsBridge Advisors, where his responsibilities include requirement gathering, solutioning, development, and productization of scalable machine learning, artificial intelligence, and analytical solutions using open source technologies. Alongside this, he supports pre-sales and competency.

    Oceny i opinie klientów: Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning Ivan Marin, Ankit Shukla, Sarang VK (0) Weryfikacja opinii następuję na podstawie historii zamówień na koncie Użytkownika umieszczającego opinię. Użytkownik mógł otrzymać punkty za opublikowanie opinii uprawniające do uzyskania rabatu w ramach Programu Punktowego.

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