Behavioural Analytics: Machine Learning Approaches for Predictive Insights
-
- Einzelkauf Download ausgewählt
-
Sprache:Englisch
Fr. 47.00
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB 3
Kopierschutz
Nein
Family Sharing
Ja
Text-to-Speech
Ja
Erscheinungsdatum
27.04.2026
Herausgeber
Shradhanjali Panda + weitereVerlag
Bentham Science PublishersSeitenzahl
242 (Printausgabe)
Dateigröße
2200 KB
Sprache
Englisch
EAN
9798898813932
Applied Machine Learning for IoT and Data Analytics (Volume 3) offers a comprehensive exploration of how machine learning transforms behavioural data into actionable intelligence. In an era where data-driven strategies shape competitive advantage, this volume examines how organisations can harness predictive analytics to understand patterns, anticipate risks, and unlock hidden opportunities.
The book introduces the foundational principles of behavioural analytics and advances into practical machine learning applications across diverse domains. It addresses critical integration challenges such as data quality, model reliability, privacy protection, and ethical considerations-highlighting transparency and responsible data governance as essential pillars of modern analytics frameworks.
Through empirical research and real-world case studies, the volume demonstrates how predictive insights can enhance employee engagement, improve customer experiences, optimise marketing performance, and support public safety initiatives. Bridging theory with applied implementation, the book equips readers with both conceptual clarity and practical strategies for deploying machine learning-driven behavioural intelligence in dynamic organisational environments.
Key Features:
-Comprehensive overview of behavioural analytics and predictive modelling foundations.
-Application of machine learning techniques with real-world perspectives on implementation and management.
-Insights into improving employee retention, customer engagement, and operational efficiency.
-Discussion of integration challenges, including data quality and governance frameworks, with a focus on ethical AI, transparency, data privacy, and responsible analytics practices
Noch keine Bewertungen vorhanden
Verfassen Sie die erste Bewertung zu diesem Artikel
Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.