Generative AI for Everyone
eBook - ePub

Generative AI for Everyone

Deep learning, NLP, and LLMs for creative and practical applications (English Edition)

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

Generative AI for Everyone

Deep learning, NLP, and LLMs for creative and practical applications (English Edition)

About this book

Description
Generative AI is revolutionizing the way we interact with technology. Imagine creating hyper-realistic images, composing original music pieces, or generating creative text formats, all with the help of AI. This book provides a comprehensive exploration of generative AI and its transformative impact across various industries.This book begins with the basics of AI, explaining ML and design patterns to build a solid foundation. It delves deeply into generative AI and then progresses through machine learning, deep learning, and essential architectures such as CNNs, GANs, Diffusion, RNNs, LSTMs, and Transformers. It covers practical applications, from regression and classification to advanced use cases such as image generation, editing, document search, content summarization, and question answering. Readers will also learn to build prototypes like a Document Q&A bot, research assistant, and prompt playground, while mastering techniques such as continued pre-training, fine-tuning, model merging, retrieval-augmented generation, and agentic AI.By the end of this book, you will transform from a curious beginner to a confident, generative AI user. You will possess the knowledge and skills to explore its capabilities for creative expression, problem-solving, and even business innovation. You will be able to confidently navigate the world of generative AI, turning your ideas into reality.

Key Features
? Explore the entire spectrum of generative AI, from fundamental AI concepts to advanced LLM applications.
? Includes practical examples, code snippets, and real-world case studies to enhance learning and understanding.
? Learn how to use generative AI for business applications, including ethical considerations.

What you will learn
? Explore concepts of AI, ML, deep learning, and generative AI.
? Learn about computer vision and generative image AI supported by coding examples.
? Discover NLP Techniques, Transformer architecture components and generative text AI supported by coding examples.
? Understand prompt engineering and LLM frameworks while building prototypes.
? Examine the role of LLM operations throughout the entire LLM lifecycle.
? Investigate the potential impact of generative AI on enterprises and develop business strategies.

Who this book is for
This book is ideal for anyone curious about generative AI, regardless of their prior technical expertise. Whether you are a business professional, a student, an artist, or simply someone fascinated by the future of technology, this book will provide you with a clear and accessible understanding of this groundbreaking field.

Table of Contents
1. AI Fundamentals
2. GenAI Foundation
3. GenAI for Images
4. Transforming Images with GenAI
5. GenAI for Text
6. ChatGPT
7. Large Language Model Frameworks
8. Large Language Model Operations
9. Generative AI for the Enterprise
10. Advances and Sustainability in Generative AI

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Yes, you can access Generative AI for Everyone by Karthikeyan Sabesan,Sivagamisundari,Nilip Dutta in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Dedication Page
  5. About the Authors
  6. About the Reviewers
  7. Acknowledgements
  8. Preface
  9. Table of Contents
  10. 1. AI Fundamentals
  11. 2. GenAI Foundation
  12. 3. GenAI for Images
  13. 4. Transforming Images with GenAI
  14. 5. GenAI for Text
  15. 6. ChatGPT
  16. 7. Large Language Model Frameworks
  17. 8. Large Language Model Operations
  18. 9. Generative AI for the Enterprise
  19. 10. Advances and Sustainability in Generative AI
  20. Index