首頁外文書商業行銷金融會計 〉Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale
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Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale

Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale


作者  /  Ofer Mendelevitch/ Casey Stella/ Douglas Eadline

出版社 / ADDISON-WESLEY PUBLISHING COMPANY

出版日期 / 2016/12/22

商品語言 / 英文

裝訂 / 平裝

定價 / NT$2,025

售價 / NT$ 2,025 ※ 特價商品,不再折扣

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Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale 其它優惠/消息


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內容簡介

The Complete Guide to Data Science with Hadoop—For Technical Professionals, Businesspeople, and Students

 

Demand is soaring for professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop® and Spark is your complete guide to doing just that. Drawing on immense experience with Hadoop and big data, three leading experts bring together everything you need: high-level concepts, deep-dive techniques, real-world use cases, practical applications, and hands-on tutorials.

 

The authors introduce the essentials of data science and the modern Hadoop ecosystem, explaining how Hadoop and Spark have evolved into an effective platform for solving data science problems at scale. In addition to comprehensive application coverage, the authors also provide useful guidance on the important steps of data ingestion, data munging, and visualization.

 

Once the groundwork is in place, the authors focus on specific applications, including machine learning, predictive modeling for sentiment analysis, clustering for document analysis, anomaly detection, and natural language processing (NLP).

 

This guide provides a strong technical foundation for those who want to do practical data science, and also presents business-driven guidance on how to apply Hadoop and Spark to optimize ROI of data science initiatives.

 

Learn

  • What data science is, how it has evolved, and how to plan a data science career
  • How data volume, variety, and velocity shape data science use cases
  • Hadoop and its ecosystem, including HDFS, MapReduce, YARN, and Spark
  • Data importation with Hive and Spark
  • Data quality, preprocessing, preparation, and modeling
  • Visualization: surfacing insights from huge data sets
  • Machine learning: classification, regression, clustering, and anomaly detection
  • Algorithms and Hadoop tools for predictive modeling
  • Cluster analysis and similarity functions
  • Large-scale anomaly detection
  • NLP: applying data science to human language







詳細資料

誠品26碼 /2681435854000
ISBN 13 /9780134024141
ISBN 10 /0134024141
EAN /9780134024141

頁數256
尺寸23.4X17.9CM
裝訂平裝
級別
語言英文
成份




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