Mohlo by sa vám tiež páčiť

Informovať o naskladnení knihy

Viac informácií o knihe Graph-Powered Machine Learning

• Parametre knihy
• Anotácia kniha
• Obľúbené z iného súdka

Nákupom získate 158 bodov

Anotácia knihy

At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed as graphs.

 

Graph-Powered Machine Learning introduces you to graph technology concepts, highlighting the role of graphs in machine learning and big data platforms. You’ll get an in-depth look at techniques including data source modeling, algorithm design, link analysis, classification, and clustering. As you master the core concepts, you’ll explore three end-to-end projects that illustrate architectures, best design practices,

optimization approaches, and common pitfalls.

 

Key Features

·   The lifecycle of a machine learning project

·   Three end-to-end applications

·   Graphs in big data platforms

·   Data source modeling

·   Natural language processing, recommendations, and relevant search

·   Optimization methods

 

Readers comfortable with machine learning basics.

 

About the technology

By organizing and analyzing your data as graphs, your applications work more fluidly with graph-centric algorithms like nearest neighbor or page rank where it’s important to quickly identify and exploit relevant relationships. Modern graph data stores, like Neo4j or Amazon Neptune, are readily available tools that support graph-powered machine learning.

 

Alessandro Negro is a Chief Scientist at GraphAware. With extensive experience in software development, software architecture, and data management, he has been a speaker at many conferences, such as Java One, Oracle Open World, and Graph Connect. He holds a Ph.D. in Computer Science and has authored several publications on graph-based machine learning.

Parametre knihy

• Celý názov: Graph-Powered Machine Learning
• Autor: Nego, Alessandro
• Jazyk: Angličtina
• Väzba: Brožovaná
• Počet strán: 503
• EAN: 9781617295645
• ISBN: 1617295647
• ID: 32939025
• Nakladateľ: Manning Publications
• Hmotnosť: 856 g
• Rozmery: 186 × 234 × 31 mm
• Dátum vydania: 28. September 2021

Obľúbené z iného súdka

---

---

---