Bộ sách luyện thi ETS 2023 LC&RC
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Thể loại:Computers - Web Development
Năm:2017
Nhà xuát bản:O’Reilly Media
Ngôn ngữ:english
Trang:352 / 351
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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