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Business Analytics for Professionals [electronic resource] / edited by Alp Ustundag, Emre Cevikcan, Omer Faruk Beyca.

Contributor(s): Material type: TextTextLanguage: İngilizce Series: Springer Series in Advanced ManufacturingPublisher: Cham : Springer International Publishing : Imprint: Springer, 2022Edition: 1st ed. 2022Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783030938239
Subject(s): LOC classification:
  • HF5548.2
Online resources:
Contents:
PART I: TBA -- Chapter 1. Business Analytics for Managers -- Chapter 2. Big Data Management and Technologies -- Chapter 3. Descriptive Analytics: Feature Engineering & Data Visualization -- Chapter 4. Predictive Analytics with Machine Learning -- Chapter 5. Neural Networks and Deep Learning -- Chapter 6. Handling Unstructured Data: Text Analytics and Image Analysis -- Chapter 7. Prescriptive Analytics: Optimization and Modelling -- PART II: TBA -- Chapter 8. Supply Chain Analytics -- Chapter 9. CRM & Marketing Analytics -- Chapter 10. Financial Analytics -- Chapter 11. Human Resources Analytics -- Chapter 12. Manufacturing Analytics.
Summary: This book explains concepts and techniques for business analytics and demonstrate them on real life applications for managers and practitioners. It illustrates how machine learning and optimization techniques can be used to implement intelligent business automation systems. The book examines business problems concerning supply chain, marketing & CRM, financial, manufacturing and human resources functions and supplies solutions in Python.
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Holdings
Item type Current library Home library Collection Call number Copy number Status Notes Date due Barcode
E-Book E-Book Merkez Kütüphane Merkez Kütüphane E-Kitap Koleksiyonu HF5548.2EBK (Browse shelf(Opens below)) 1 Geçerli değil-e-Kitap / Not applicable-e-Book END EBK02854

PART I: TBA -- Chapter 1. Business Analytics for Managers -- Chapter 2. Big Data Management and Technologies -- Chapter 3. Descriptive Analytics: Feature Engineering & Data Visualization -- Chapter 4. Predictive Analytics with Machine Learning -- Chapter 5. Neural Networks and Deep Learning -- Chapter 6. Handling Unstructured Data: Text Analytics and Image Analysis -- Chapter 7. Prescriptive Analytics: Optimization and Modelling -- PART II: TBA -- Chapter 8. Supply Chain Analytics -- Chapter 9. CRM & Marketing Analytics -- Chapter 10. Financial Analytics -- Chapter 11. Human Resources Analytics -- Chapter 12. Manufacturing Analytics.

This book explains concepts and techniques for business analytics and demonstrate them on real life applications for managers and practitioners. It illustrates how machine learning and optimization techniques can be used to implement intelligent business automation systems. The book examines business problems concerning supply chain, marketing & CRM, financial, manufacturing and human resources functions and supplies solutions in Python.

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