Data science

by Lillian Pierson ; foreword by Jake Porway, founder and executive director of DataKind
2nd edition. Hoboken, NJ : John Wiley and Sons, Inc, [2017]
xvi, 364 pages ; 24 cm.
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English CollectionT58.5 .P488 2017A1868394Available

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Record details

    • Begins by explaining large data sets and data formats, including sample Python code for manipulating data. The book explains how to work with relational databases and unstructured data, including NoSQL. The book then moves into preparing data for analysi
    • Getting Started With Data Science
    • Wrapping Your Head around Data Science
    • Exploring Data Engineering Pipelines and Infrastructure
    • Applying Data-Driven Insights to Business and Industry
    • Using Data Science to Extract Meaning from Your Data
    • Machine Learning: Learning from Data with your Machine
    • Math, Probability, and Statistical Modeling
    • Using Clustering to Subdivide Data
    • Modeling with Instances
    • Building models that Operate Internet-of-Things Devices
    • Creating Data Visualizations that Clearly Communicate Meaning
    • Following the Principles of Data Visualization Design
    • Using D3.js for Data Visualization
    • Web-Based Applications for Visualization Design
    • Exploring Best Practices in Dashboard Design
    • Making Maps from Spatial Data
    • Computing for Data Science
    • Using Python for Data Science
    • Using Open Source R for Data Science
    • Using SQL in Data Scienc
    • illustrations, charts
    • Includes index.
    • John Wiley and Sons, Inc
    • 1119327636 (paperback)
    • 9781119327639 (paperback)
    • 2017932294
    • text
    • still image
    • volume
    • online resource
    • computer
    • https://www.sls.org.hk:8443/opac/bib/ABlW
    • View MARC record
    • View BIBFRAME linked data