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Agile Data Science 2.0

Building Full-stack Data Analytics Applications with Spark

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  • 352 strony
  • 13 godzin czytania

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"Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they?re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You?ll learn an iterative approach that lets you quickly change the kind of analysis you?re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization"--Back cover

Zakup książki

Agile Data Science 2.0, Jurney Russell

Język
Rok wydania
2017
Oprawa
(miękka)
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Tytuł
Agile Data Science 2.0
Podtytuł
Building Full-stack Data Analytics Applications with Spark
Język
angielski
Wydawca
O'Reilly
Rok wydania
2017
Oprawa
miękka
Liczba stron
352
ISBN10
1491960116
ISBN13
9781491960110
Seria
Ocena
3,55 z 5
Opis
"Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they?re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You?ll learn an iterative approach that lets you quickly change the kind of analysis you?re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization"--Back cover