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Graph Algorithms: Practical Examples in Apache , Needham, Hodler+=
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Numero oggetto eBay:313256516608
Specifiche dell'oggetto
- Condizione
- PublishedOn
- 2019-05-31
- Title
- Graph Algorithms: Practical Examples in Apache Spark and Neo4j
- Artist
- Not Specified
- ISBN
- 9781492047681
- Subject Area
- Mathematics, Computers
- Publication Name
- Graph Algorithms : Practical Examples in Apache Spark and Neo4j
- Publisher
- O'reilly Media, Incorporated
- Item Length
- 9.2 in
- Subject
- Computer Graphics, Programming / Algorithms, Intelligence (Ai) & Semantics, Algebra / General
- Publication Year
- 2019
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Height
- 0.8 in
- Item Weight
- 18 Oz
- Item Width
- 7 in
- Number of Pages
- 265 Pages
Informazioni su questo prodotto
Product Identifiers
Publisher
O'reilly Media, Incorporated
ISBN-10
1492047686
ISBN-13
9781492047681
eBay Product ID (ePID)
25038750783
Product Key Features
Number of Pages
265 Pages
Publication Name
Graph Algorithms : Practical Examples in Apache Spark and Neo4j
Language
English
Publication Year
2019
Subject
Computer Graphics, Programming / Algorithms, Intelligence (Ai) & Semantics, Algebra / General
Type
Textbook
Subject Area
Mathematics, Computers
Format
Trade Paperback
Dimensions
Item Height
0.8 in
Item Weight
18 Oz
Item Length
9.2 in
Item Width
7 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2019-275313
Illustrated
Yes
Synopsis
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 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, 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, 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 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
LC Classification Number
QA166.245.N44 2019
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