Build a text-to-image generator (from scratch) / Mark Liu.

Format:

Video

Author/Creator:

Liu, Mark (Mark H.), author.

Contributor:

Manning Publications, publisher.

Language:

English

Subjects (All):

Application software--Development.

Application software.

Natural language generation (Computer science)--Computer programs.

Natural language generation (Computer science).

Artificial intelligence.

Computer graphics.

Physical Description:

1 online resource (1 video file (09 hr., 37 min.)) : sound, color.

Edition:

Video Edition.

[First edition].

Place of Publication:

[Shelter Island, New York] : Manning Publications, 2025.

Summary:

Build your own vision transformer and diffusion models for text-to-image generation-from scratch! Build a Text-to-Image Generator (from Scratch) takes you step-by-step through creating your own AI models that can generate images from text. You'll explore two methods of image generation--vision transformers and diffusion models--and learn vital AI development techniques as you go. Build a Text-to-Image Generator (from Scratch) teaches you how to: Build and train models to generate high resolution images based on text descriptions Edit an existing image based on text prompts Build and train a model to add captions to images Build and train a vision transformer to classify images Fine-tune LLMs for downstream tasks such as classification, text or image generation Better differentiate real images from deepfakes Build a Text-to-Image Generator (from Scratch) dives into the powerful models behind AI image generators. The best way to learn is to build something from scratch, and in this book you'll build your very own diffusion model and vision transformer. As you work through each stage of development, you'll develop an understanding of how these models can be customized, applied, and integrated for impressive multimodal AI. About the Technology AI-generated images appear everywhere from high-end advertising to casual social media feeds. Text-to-image tools like Dall-e, Midjourney, and Flux make it easy to create AI art, but how do they work? In this book, you'll find out by building your own text-to-image generator! About the Book Build a Text-to-Image Generator (from Scratch) explores both transformer-based image generation and diffusion models. You'll work hands-on to build a pair of simple generation models that can classify images, automatically add captions, reconstruct images, and enhance existing graphics. Author Mark Liu guides you every step of the way with clear explanations, informative diagrams, and eye-opening examples you can build on your own laptop. What's Inside Build a vision transformer to classify images Edit images using text prompts Fine-tune image models About the Reader Requires basic knowledge of generative AI models and intermediate Python skills. About the Author Mark Liu is the founding director of the Master of Science in Finance program at the University of Kentucky. He is also the author of Learn Generative AI with PyTorch. Quotes A practical and readable introduction with working code and clear explanations. - Andrey Lukyanenko, Meta Empowers you to unlock creativity at the intersection of text and imagery. - Bojan Tunguz, Tabul.AI Amazingly comprehensive, hype-free, hands-on, and code-rich guidebook. - Kirk Borne, Data Leadership Group Successfully brings together the theoretical foundations and practical applications, from transformers to diffusion models. - Raymond Cheung, Parity Technologies.

Notes:

OCLC-licensed vendor bibliographic record.

OCLC:

1569718399

Publisher Number:

9781633435421VE