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portada Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark
Type
Physical Book
Author
Publisher
Language
English
Pages
349
Format
Paperback
Dimensions
23.1 x 17.8 x 1.8 cm
Weight
0.54 kg.
ISBN13
9781491960110
Categories

Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark

Russell Jurney (Author) · O'Reilly Media · Paperback

Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark - Jurney, Russell

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Synopsis "Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark"

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. Build value from your data in a series of agile sprints, using the data-value pyramid Extract features for statistical models from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future via classification and regression Translate predictions into actions Get feedback from users after each sprint to keep your project on track

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