Hands-On Graph Analytics with Neo4j : Perform Graph Processing and Visualization Techniques Using Connected Data Across Your Enterprise /
Contiene: Sección I. Modelado de gráficos con Neo4j: 1) Bases de datos de grafos; 2) El lenguaje de consulta Cypher; 3) Potenciando su negocio con Pure Cypher. Sección II. Algoritmos gráficos: 4) La biblioteca de ciencia de datos Graph y la búsqueda de rutas; 5) Datos espaciales; 6) Importancia del...
I tiakina i:
| Kaituhi matua: | |
|---|---|
| Hōputu: | Pukapuka |
| Reo: | Ingarihi |
| I whakaputaina: |
Birmingham, Inglaterra :
Packt,
2020, c2020
|
| Ngā marau: | |
| Urunga tuihono: | Ver documento en línea |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
|
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- Graph Data Science with Neo4j : Learn How to Use Neo4j 5 with Graph Data Science Library 2.0 and Its Python Driver for Your Project /
- Graph Data Science with Python and Neo4j : Hands-on Projects on Python and Neo4j Integration for Data Visualization and Analysis Using Graph Data Science for Building Enterprise Strategies /
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow : Concepts, Tools, and Techniques to Build Intelligent Systems /
- Hands-On Natural Language Processing with Python : A Practical Guide to Applying Deep Learning Architectures to Your NLP Applications /
- Graph Algorithms : Practical Examples in Apache Spark and Neo4j /