Challenges and Applications of Data Analytics in Social Perspectives

Challenges and Applications of Data Analytics in Social Perspectives
PDF
  • eBook:
    Challenges and Applications of Data Analytics in Social Perspectives
  • Author:
    V. Sathiyamoorthi, Atilla Elci
  • Edition:
    1 edition
  • Categories:
  • Data:
    December 4, 2020
  • ISBN:
    1799825663
  • ISBN-13:
    9781799825661
  • Language:
    English
  • Pages:
    324 pages
  • Format:
    PDF

Book Description
With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress.
Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students.

Content

Chapter 1. A Comprehensive Review of Professional Network Impact on Education and Career
Chapter 2. A Comprehensive Survey of Data Mining Techniques in Disease Prediction
Chapter 3. Analysis of Crime Report by Data Analytics Using Python
Chapter 4. Analysis on Indian Stock Market Prediction Using Deep Learning Models
Chapter 5. Application of Data Analytics in Emerging Fields
Chapter 6. Architecture for Analyzing Agriculture Data Using Data Analytics
Chapter 7. Automated Soil Residue Levels Detecting Device With IoT Interface
Chapter 8. Biofeedback-Based Mental Health Software and Its Statistical Analysis
Chapter 9. Social Media Content Analysis: Machine Learning
Chapter 10. Challenges and Applications of Recommender Systems in E-Commerce
Chapter 11. Language Classification and Recognition From Audio Using Deep Belief Network
Chapter 12. Machine Learning Approach: Enriching the Knowledge of Ayurveda From Indian Medicinal Herbs
Chapter 13. Machine Learning for Business Analytics
Chapter 14. A Comprehensive Study of Data Analytics in Social Perspectives
Chapter 15. Patient Monitoring System Using Internet of Things

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