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A Beginner’s Guide to Generative AI : An Introductory Path to Diffusion Models, ChatGPT, and LLMs / by Deepshikha Bhati, Fnu Neha, Angela Guercio, Md Amiruzzaman, Aloysius Bathi Kasturiarachi.
Springer Nature - Synthesis Collection of Technology (R0) eBook Collection 2026 Available online
View online- Format:
- Book
- Author/Creator:
- Bhati, Deepshikha.
- Series:
- Synthesis Lectures on Computer Science, 1932-1686
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Machine learning.
- Natural language processing (Computer science).
- Computational linguistics.
- Quantitative research.
- Computer science.
- Artificial Intelligence.
- Machine Learning.
- Natural Language Processing (NLP).
- Computational Linguistics.
- Data Analysis and Big Data.
- Computer Science.
- Local Subjects:
- Artificial Intelligence.
- Machine Learning.
- Natural Language Processing (NLP).
- Computational Linguistics.
- Data Analysis and Big Data.
- Computer Science.
- Physical Description:
- 1 online resource (240 pages)
- Edition:
- 1st ed. 2026.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2026.
- Summary:
- This book is the essential guide for anyone curious about AI’s creative power. In the rapidly evolving landscape of artificial intelligence, generative AI stands out as one of the most transformative technologies of our time. Designed for beginners and requiring no prior knowledge of AI, this book breaks down the fundamentals of generative AI, from text and image generation to the workings of models like ChatGPT and Google Bard. The authors provide step-by-step coverage of the essential concepts and techniques that power generative AI. From the basics of how machines learn to generate text and images, to the intricate workings of models like Transformers, ChatGPT, and Google Bard, readers will gain a solid foundation in AI's most cutting-edge tools. Rather than focusing on a single method, the authors introduce a spectrum of generative modeling techniques, including diffusion models, variational autoencoders, and transformers. This comprehensive exposure ensures readers will be well-prepared to understand and adapt to the rapidly evolving AI landscape. In addition, real-world applications of generative AI across various industries are explored including healthcare innovations, business analytics, and legal technology, and the authors provide practical insights and examples that show how generative AI is revolutionizing these fields. In addition, this book: Offers a thorough, accessible, and engaging introduction to one of the most exciting areas of technology today Covers a diverse range of generative modeling techniques, from transformers to variational autoencoders Includes multiple-choice exercise questions and summaries at the end of each chapter to reinforce learning.
- Contents:
- Introduction to Generative AI
- Evolution of Neural Networks to Large Language Models
- LLMs and Transformers
- The ChatGPT Architecture: An In-Depth Exploration of OpenAI
- Google Bard and Beyond
- Diffusion Model and Generative AI for Images
- Setting Up the Environment and Implementing LLMs
- ChatGPT Use Cases.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 3-031-84724-5
- OCLC:
- 1528956432
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