Description
| Product ID: | 9781617299469 |
| Product Form: | Paperback / softback |
| Country of Manufacture: | GB |
| Title: | Graph Algorithms for Data Science |
| Authors: | Author: Tomaz Bratanic |
| Page Count: | 325 |
| Subjects: | Algorithms and data structures, Algorithms & data structures, Software Engineering, Databases, Maths for computer scientists, Software Engineering, Databases, Maths for computer scientists |
| Description: | Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You''ll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications. It''s filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You''ll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn:
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. It''s filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You''ll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don''t need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technologyGraphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations.about the bookGraph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You''ll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you''ll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks. |
| Imprint Name: | Manning Publications |
| Publisher Name: | Manning Publications |
| Country of Publication: | GB |
| Publishing Date: | 2024-02-06 |
