| Description |
1 online resource (xv, 458 pages) : illustrations (some color) |
| Contents |
Intro -- Table of Contents -- About the Authors -- About the Technical Reviewer -- Introduction -- Chapter 1: Introduction to Generative AI -- Unveiling the Magic of Generative AI -- The Genesis of Generative AI -- Milestones Along the Way -- Fundamentals of Generative Models -- Neural Networks: The Backbone of Generative AI -- Key Neural Network Architectures Relevant to Generative AI -- Convolutional Neural Networks -- Recurrent Neural Networks -- Generative Adversarial Networks -- Transformers -- Understanding the Difference: Generative vs. Discriminative Models |
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Understanding the Core: Types and Techniques -- Diffusion Models -- Generative Adversarial Networks -- Variational Autoencoders -- Restricted Boltzmann Machines -- Pixel Recurrent Neural Networks -- Generative Models in Society and Technology -- Real-World Applications and Advantages of Generative AI -- Ethical and Technical Challenges of Generative AI -- DeepMind's Approach to Data Privacy and Security -- Impact of Generative Models in Data Science -- The Diverse Domains of Generative AI -- Visuals: From Pixel to Palette -- Audio: Symphonies of AI -- Text: Weaving Words into Worlds |
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The Future of Generative AI: A Symphony of Possibilities -- Setting Up the Development Environment -- Setting Up a Google Colab Environment -- Hugging Face Access and Token Key Generation -- OpenAI Access Account and Token Key Generation -- Troubleshooting Common Issues -- Summary -- Chapter 2: Text-to-Image Generation -- Introduction -- Bridging the Gap Between Text and Image Data -- Understanding the Fundamentals of Image Data -- Correlation Between Image and Text Data Using CLIP Model -- Architecture and Functioning -- CLIP Case Study -- Implementation of CLIP |
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Step 1: Installing Libraries and Data Loading -- Step 2: Data Preprocessing -- Step 3: Model Inference -- Diffusion Model -- Implement Diffusion Model from Scratch -- Step 1: Installing Libraries -- Step 2: Data Preprocessing -- Step 3: Model Training -- Text-to-Image Generation -- Using a Pre-trained Model -- Step 1: Installing Libraries -- Step 2: Model Inference -- Fine-Tuning Text-to-Image Models -- Step 1: Installing Libraries and Data Loading -- Step 2: Model Training -- Step 3: Model Inference -- Common Challenges and Troubleshooting Tips -- Conclusion |
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Chapter 3: From Script to Screen: Unveiling Text-to-Video Generation -- Introduction -- Understanding Video Data -- Challenges in Working with Video Data -- The Synergy of Video and Textual Data -- Tagging Videos with Semantic Metadata -- Hands-On: Demonstrating a Pre-Trained Model -- Step 1: Installing Libraries -- Step 2: Model Inference -- Fine-Tuning for Custom Applications -- Step 1: Installing Libraries -- Step 2: Data Loading and Preprocessing -- Step 3: Model Training (Fine-Tuning) -- Step 4: Model Inference -- Conclusion -- Chapter 4: Bridging Text and Audio in Generative AI |
| Summary |
This book explains the field of Generative Artificial Intelligence (AI), focusing on its potential and applications, and aims to provide you with an understanding of the underlying principles, techniques, and practical use cases of Generative AI models. The book begins with an introduction to the foundations of Generative AI, including an overview of the field, its evolution, and its significance in today's AI landscape. It focuses on generative visual models, exploring the exciting field of transforming text into images and videos. A chapter covering text-to-video generation provides insights into synthesizing videos from textual descriptions, opening up new possibilities for creative content generation. A chapter covers generative audio models and prompt-to-audio synthesis using Text-to-Speech (TTS) techniques. Then the book switch gears to dive into generative text models, exploring the concepts of Large Language Models (LLMs), natural language generation (NLG), fine-tuning, prompt tuning, and reinforcement learning. The book explores techniques for fixing LLMs and making them grounded and indestructible, along with practical applications in enterprise-grade applications such as question answering, summarization, and knowledge-based generation. By the end of this book, you will understand Generative text, and audio and visual models, and have the knowledge and tools necessary to harness the creative and transformative capabilities of Generative AI. What You Will Learn What is Generative Artificial Intelligence? What are text-to-image synthesis techniques and conditional image generation? What is prompt-to-audio synthesis using Text-to-Speech (TTS) techniques? What are text-to-video models and how do you tune them? What are large language models, and how do you tune them? Who This Book Is For Those with intermediate to advanced technical knowledge in artificial intelligence and machine learning |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Description based on online resource; title from digital title page (viewed on August 06, 2024) |
| Subject |
Artificial intelligence.
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artificial intelligence.
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| Form |
Electronic book
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| Author |
Khublani, Drupad K., author
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| ISBN |
9798868804038 |
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