- Main
- Computers - Computer Science
- Graph Algorithms: Practical Examples in...
Graph Algorithms: Practical Examples in Apache Spark and Neo4j
Mark Needham, Amy E. HodlerQuanto ti piace questo libro?
Qual è la qualità del file?
Scarica il libro per la valutazione della qualità
Qual è la qualità dei file scaricati?
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
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
Categorie:
Anno:
2019
Edizione:
1
Casa editrice:
O’Reilly Media
Lingua:
english
Pagine:
256
ISBN 10:
1492047686
ISBN 13:
9781492047681
File:
PDF, 10.24 MB
I tuoi tag:
IPFS:
CID , CID Blake2b
english, 2019
Leggi Online
- Scaricare
- pdf 10.24 MB Current page
- Checking other formats...
- Convertire a
- Sbloccare file di conversione di dimensioni maggiori di 8 MB Premium
Il file verrà inviato al tuo indirizzo email. Ci vogliono fino a 1-5 minuti prima di riceverlo.
Entro 1-5 minuti il file verrà consegnato al tuo account Telegram.
Attenzione: assicurati di aver collegato il tuo account al bot Z-Library Telegram.
Entro 1-5 minuti il file verrà consegnato al tuo dispositivo Kindle.
Nota: devi verificare ogni libro che desideri inviare al tuo Kindle. Controlla la tua casella di posta per l'e-mail di verifica da Amazon Kindle Support.
La conversione in è in corso
La conversione in non è riuscita
Vantaggi dello status Premium
- Inviare a lettori di e-book
- Limite aumentato di download
- Converti i file
- Più risultati di ricerca
- Altri vantaggi