Generative AI and Creativity
eBook - ePub

Generative AI and Creativity

From Theory to Practice

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Generative AI and Creativity

From Theory to Practice

About this book

Generative AI and Creativity: From Theory to Practice is an immersive exploration into the revolutionary domain of generative artificial intelligence. It takes a step-by-step journey starting with the fundamentals of generative AI and progressing to advanced applications. The book unravels the complexities of generative models, delving into key techniques such as generative adversarial networks (GANs) and variational autoencoders (VAE)s, providing a solid foundation for readers to understand the underlying principles.

FEATURES

ā€¢ Explores the collaboration between humans and AI in creative processes

ā€¢ Examines generative art movements, graphic design applications, and artist-AI collaborations

ā€¢ Defines creativity in AI, by showcasing case studies and discussing ethical considerations

Moving beyond creative content generation in art and music to practical implementations in industries like healthcare and finance, the book showcases the versatility and transformative potential of generative AI across diverse domains. Readers will gain practical skills through coding examples, case studies, and collaborative projects, empowering them to integrate generative AI into their own work.

The book is enriched with stories of innovation, featuring pioneers who have leveraged generative AI to push the boundaries of creativity. Ethical considerations and the societal impact of generative AI are also explored to foster a holistic understanding of the technology.

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Yes, you can access Generative AI and Creativity by Elakkiya Rajasekar,Subramaniyaswamy V in PDF and/or ePUB format, as well as other popular books in Computer Science & Art General. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title
  4. Copyright
  5. Contents
  6. Preface
  7. Editors
  8. Contributors
  9. Chapter 1 Generative AI and Creativity: An Overview
  10. Chapter 2 Understanding Creativity Using Generative AI: In-Depth Analysis
  11. Chapter 3 Harmonizing Tradition and Innovation: Computational Strategies for Preserving Thanjavur Paintings from Generative AI
  12. Chapter 4 Creation and Analysis of Sculptures Using the Principles of Generative AI
  13. Chapter 5 An Automated Image Style Transfer Framework Using GenAI Algorithm
  14. Chapter 6 Human-AI Collaboration with Decision Control and Adaptive Trust for Enhancing User Perceptions
  15. Chapter 7 Applications of Generative AI in Gaming and Virtual Environments
  16. Chapter 8 EffiTrans Basal Cell Carcinoma: Designing a Generative AI Framework for Accurate Basal Cell Carcinoma Image Classification Using EfficientNet and Transfer Learning
  17. Chapter 9 Generative AIā€“Driven Music Genre Classification: Unlocking Creativity and Innovation in Automated Audio Analysis
  18. Chapter 10 Image-Based Analysis of Parkinsonā€™s Disease Using Generative Artificial Intelligence Algorithms
  19. Chapter 11 Harnessing Generative AI Tools and Techniques: Beyond Algorithms for a Smarter Future
  20. Chapter 12 An Exploration of Generative AI Frameworks and Tools for Generation of Multi-Perspective Contents
  21. Chapter 13 Comprehensive Understanding of Evaluating and Testing Generative Models
  22. Chapter 14 Metrics, Tools and Challenges for Assessing Generative Models
  23. Chapter 15 Rise of Generative AI: Exploring Its Impact on Creative Industries
  24. Chapter 16 Impact of Commercial Applications on GenAI with Its Evolving Landscape
  25. Chapter 17 AI in Academic Environments: A Study of Perspectives and Practices
  26. Chapter 18 Generative AI: A Personalized and Ubiquitous Tutor
  27. Chapter 19 Integration of Generative AI: An Advent of Education 4.0
  28. Chapter 20 Generative AI ā€“ Challenges and Future Directions
  29. Chapter 21 Comparative Analysis of Transformer Models for Stack Overflow Question Quality Classification
  30. Index