TY  - BOOK
AU  - Bratanic,Tomaz
TI  - Graph algorithms for data science: with examples in Neo4j 
SN  - 9781617299469
U1  - 006.31 
PY  - 2024///
CY  - Shelter Island
PB  - Manning
KW  - Graph algorithms
KW  - Machine learning
N1  - Includes bibliographical references and index
N2  - Labeled-property graph modeling Constructing a graph from structured data such as CSV or SQL NLP techniques to construct a graph from unstructured data Cypher query language syntax to manipulate data and extract insights Social network analysis algorithms like PageRank and community detection How to translate graph structure to a ML model input with node embedding models Using graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis
ER  -