9780134024141 - Practical Data Science With Hadoop and Spark: Designing and Building Effective Analytics at Scale di Mendelevitch, Ofer; Stella, Casey; Eadline, Doug (22 risultati)

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Paperback. Condizione: new. Paperback. This book provides a unique perspective on applying data science with Hadoop by explaining what data science with Hadoop is all about, its practical business applications, and then diving deep into the details and providing a hands-on tutorial and showcase of various use-cases from the real world. The authors bring together all the practical knowledge students will need to do real, useful data science with Hadoop. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Condizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

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Paperback. Condizione: Brand New. 400 pages. 9.25x7.25x0.75 inches. In Stock.

Paperback. Condizione: new. Paperback. This book provides a unique perspective on applying data science with Hadoop by explaining what data science with Hadoop is all about, its practical business applications, and then diving deep into the details and providing a hands-on tutorial and showcase of various use-cases from the real world. The authors bring together all the practical knowledge students will need to do real, useful data science with Hadoop. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condizione: Neu. Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale | Ofer Mendelevitch (u. a.) | Taschenbuch | 256 S. | Englisch | 2017 | Pearson | EAN 9780134024141 | Verantwortliche Person für die EU: Pearson Studium im Verlag Pearson Benelux B.V. Zweigniederla, Sankt-Martin-Str. 82, 81541 München, buchhandel[at]pearson[dot]com | Anbieter: preigu.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 256 pp. Englisch.

Condizione: New. Print on Demand pp. 400.

Condizione: New. Print on Demand pp. 400.

Condizione: New. PRINT ON DEMAND pp. 400.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides a unique perspective on applying data science with Hadoop by explaining what data science with Hadoop is all about, its practical business applications, and then diving deep into the details and providing a hands-on tutorial and showcase .

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The Complete Guide to Data Science with HadoopFor 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 languageFinancial Times Prent., St.-Martin-Straße 82, 81541 München 256 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.