New Age Analytics

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Luna, Alvin Albuero De
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Ashland : Arcler Press, 2020.
Temas:
Machine learning.
Data mining.
Big data.
Apprentissage automatique.
Exploration de données (Informatique)
Données volumineuses.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright
  • ABOUT THE AUTHOR
  • TABLE OF CONTENTS
  • Glossary
  • List of Figures
  • List of Tables
  • List of Abbreviations
  • Preface
  • Chapter 1 Analysis and Its Techniques
  • 1.1. Introduction
  • 1.2. Eight Types of Analysis In Research
  • 1.3. Phases in Analysis
  • 1.4. DA Methods
  • 1.5. Qualitative Data
  • 1.6. Quantitative Data
  • 1.7. Considerations/Issues In Data Analysis
  • 1.8. Conclusion
  • References
  • Chapter 2 Digital Marketing And Analytics
  • 2.1. Introduction
  • 2.2. Defining Digital Marketing
  • 2.3. Understanding The Importance Of Digital Marketing
  • 2.4. Dashboard Metrics
  • 2.5. The 5Ds Of Digital Marketing
  • 2.6. Principles Of Digital Marketing
  • 2.7. Digital Marketing Analytics Tools
  • 2.8. Why Digital Marketing Analytics Matter To Your Business
  • 2.9. How To Use Analytics In Digital Marketing
  • 2.10. Importance Of Digital Marketing Analytics
  • 2.11. The Present And Future Of Marketing Analytics
  • 2.12. The Future Of Analytics And How It's Changing Digital Marketing
  • 2.13. Conclusion
  • References
  • Chapter 3 Introduction To Artificial Intelligence
  • 3.1. Introduction
  • 3.2. What Is Artificial Intelligence?
  • 3.3. Impacts Of Artificial Intelligence In Everyday Life
  • 3.4. Artificial Intelligence Permeation And Application
  • 3.5. Applications Of Artificial Intelligence
  • 3.6. Artificial Intelligence: Cause Of Unemployment
  • 3.7. Dangers Of Artificial Intelligence
  • 3.8. General Artificial Intelligence Can Go Against Humans In The Following Ways
  • 3.9. Advantages And Disadvantages Of Artificial Intelligence
  • 3.10. Conclusion
  • References
  • Chapter 4 Machine Learning: Tools And Techniques
  • 4.1. Introduction
  • 4.2. Machine Learning Methods
  • 4.3. Machine Learning Tools
  • 4.4. Why Use Tools
  • 4.5. Tools With A Purpose
  • 4.6. How Does This Serve In Delivering Results In A Machine Learning Project?
  • 4.7. When To Use Machine Learning Tools
  • 4.8. Platforms Versus Libraries
  • 4.9. Examples Of Machine Learning Platforms Are
  • 4.10. Learning Techniques
  • 4.11. Programming Languages
  • 4.12. Human Biases
  • 4.13 Frameworks For General Machine Learning
  • 4.14. Deep Learning: A Part Of Machine Learning
  • 4.15. Untapped Opportunities Of Deep Learning
  • 4.16. Deep Learning -Disadvantages
  • 4.17. Conclusion
  • References
  • Chapter 5 Social Media Analytics
  • 5.1. Introduction
  • 5.2. Social Media Analytics
  • 5.3. The Need For Social Media Analytics
  • 5.4. Challenges Of Using Social Media Analytics
  • 5.5. The Importance Of Social Media Analytics
  • 5.6. The Social Media Analytics Process
  • 5.7. Social Media Analytic Techniques
  • 5.8. The Social Media Analytics And Value
  • 5.9. Conclusion
  • References
  • Chapter 6 Business Analytics: Its Application Through IoT
  • 6.1. Introduction
  • 6.2. What Is Business Analytics?
  • 6.3. Advantages Of Business Analytics
  • 6.4. Business Analytics: Applications

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