Übersicht			Auf mobile öffnen

Lieferstatus:	i.d.R. innert 7-14 Tagen versandfertig
Veröffentlichung:	November 2023
Genre:	Wirtschaft / Recht
	COMPUTERS / Database Administration & Management / Data analysis# general / Data Capture & Analysis / Data capture and analysis / Data science and analysis# general / For graduate / post-graduate and equivalents / machine learning / Textbook, coursework
ISBN:	9781009318259
EAN-Code:	9781009318259
Verlag:	Cambridge Academic
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 245 mm / B 170 mm / D 20 mm
Gewicht:	780 gr
Illustration:	Worked examples or Exercises
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

Based on the authors' extensive teaching experience, this hands-on graduate-level textbook teaches how to carry out large-scale data analytics and design machine learning solutions for big data. With a focus on fundamentals, this extensively class-tested textbook walks students through key principles and paradigms for working with large-scale data, frameworks for large-scale data analytics (Hadoop, Spark), and explains how to implement machine learning to exploit big data. It is unique in covering the principles that aspiring data scientists need to know, without detail that can overwhelm. Real-world examples, hands-on coding exercises and labs combine with exceptionally clear explanations to maximize student engagement. Well-defined learning objectives, exercises with online solutions for instructors, lecture slides, and an accompanying suite of lab exercises of increasing difficulty in Jupyter Notebooks offer a coherent and convenient teaching package. An ideal teaching resource for courses on large-scale data analytics with machine learning in computer/data science departments.