000			01776nam a2200193 4500
999			_c64979 _d64979
008			200530b2019 ||||| |||| 00| 0 eng d
020			_a9789352138487
082			_a511.5 NEE-M
100			_aNeedham, Mark
245			_aGraph Algorithms / _cMark Needham and Amy E. Hodler
260			_aIndia _bShroff Publishers _c2019
300			_a235 p.
440			_aINR _v950.00.
500			_alearn 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.<Br> 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. <Br> Learn how graph analytics reveal more predictive elements in today’s data <understand how popular graph algorithms work and how they've 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 work flow for link prediction by combining Neo4j and Spark.
650			_aSpark (Electronic resource : Apache Software Foundation)
650			_aGraph algorithms
650			_aWeb applications
650			_aApplication software--Development