ISBN: 9781492047681 - graph algorithms: practical examples in apache spark and neo4j (17 Ergebnisse)

- Softcover
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Paperback. Zustand: Good. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether theyre used for building dynamic network models or forecasting real-world behavior.

- Softcover
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Paperback. Zustand: New. Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world behavior. Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns-from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics. Learn how graph analytics reveal more predictive elements in today's data Understand how popular graph algorithms work and how they're applied Use sample code and tips from more than 20 graph algorithm examples Learn which algorithms to use for different types of questions Explore examples with working code and sample datasets for Spark and Neo4j Create an ML workflow for link prediction by combining Neo4j and Spark.…

- Softcover
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

- Softcover
Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes KönigreichRarewaves.com USA
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Paperback. Zustand: New. Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world behavior. Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns-from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics. Learn how graph analytics reveal more predictive elements in today's data Understand how popular graph algorithms work and how they're applied Use sample code and tips from more than 20 graph algorithm examples Learn which algorithms to use for different types of questions Explore examples with working code and sample datasets for Spark and Neo4j Create an ML workflow for link prediction by combining Neo4j and Spark.…

- Softcover
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- Softcover
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- Softcover
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Zustand: New.

- Softcover
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Paperback. Zustand: Brand New. 235 pages. 9.25x7.00x0.75 inches. In Stock.

- Softcover
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Zustand: New. pp. 268.

- Softcover
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Zustand: New. In English.

- Softcover
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Paperback. Zustand: New. Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world behavior. Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns-from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics. Learn how graph analytics reveal more predictive elements in today's data Understand how popular graph algorithms work and how they're applied Use sample code and tips from more than 20 graph algorithm examples Learn which algorithms to use for different types of questions Explore examples with working code and sample datasets for Spark and Neo4j Create an ML workflow for link prediction by combining Neo4j and Spark.…

- Softcover
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes KönigreichGreatBookPricesUK
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- Softcover
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Zustand: New. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they re used for building dynamic network models or forecasting real-world behavior.Über den AutorrnrnMark Needha.

- Softcover
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Zustand: New. 2019. Paperback. . . . . . Books ship from the US and Ireland.

- Softcover
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Taschenbuch. Zustand: Neu. Neuware - Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide,developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world behavior.Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patternsfrom finding vulnerabilities and bottlenecksto detecting communities and improving machine learning predictions. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics.- Learn how graph analytics reveal more predictive elements in today's data- Understand how popular graph algorithms work and how they're applied- Use sample code and tips from more than 20 graph algorithm examples- Learn which algorithms to use for different types of questions- Explore examples with working code and sample datasets for Spark and Neo4j- Create an ML workflow for link prediction by combining Neo4j and Spark. …

- Softcover
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Paperback. Zustand: new. Paperback. Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world behavior. Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns-from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics. Learn how graph analytics reveal more predictive elements in today's data Understand how popular graph algorithms work and how they're applied Use sample code and tips from more than 20 graph algorithm examples Learn which algorithms to use for different types of questions Explore examples with working code and sample datasets for Spark and Neo4j Create an ML workflow for link prediction by combining Neo4j and Spark" With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether theyre used for building dynamic network models or forecasting real-world behavior. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. …

- Softcover
Anbieter: Rarewaves.com UK, London, Vereinigtes KönigreichRarewaves.com UK
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EUR 62,99
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Paperback. Zustand: New. Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world behavior. Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns-from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics. Learn how graph analytics reveal more predictive elements in today's data Understand how popular graph algorithms work and how they're applied Use sample code and tips from more than 20 graph algorithm examples Learn which algorithms to use for different types of questions Explore examples with working code and sample datasets for Spark and Neo4j Create an ML workflow for link prediction by combining Neo4j and Spark.…