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

By Douglas Eadline

Product Image: 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

By Douglas Eadline

0 - Used - very good
Description
The Complete Guide to Data Science with Hadoop—For Technical Professionals, Businesspeople, and StudentsDemand 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.LearnWhat data science is, how it has evolved, and how to plan a data science careerHow data volume, variety, and velocity shape data science use casesHadoop and its ecosystem, including HDFS, MapReduce, YARN, and SparkData importation with Hive and SparkData quality, preprocessing, preparation, and modelingVisualization: surfacing insights from huge data setsMachine learning: classification, regression, clustering, and anomaly detectionAlgorithms and Hadoop tools for predictive modelingCluster analysis and similarity functionsLarge-scale anomaly detectionNLP: applying data science to human language
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
256
Release Date:
2016-12-12
Publication Date:
2016-12-12
Publisher:
Pearson International
Languages:
Original: English
ISBN10:
0134024141
ISBN13:
9780134024141
GPSR Manufacturer Reference:
[email protected]
Weight:
446 g
Height:
178 cm
Width:
232 cm
Thickness:
15 cm
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