Programming generative AI

• Titel: Programming generative AI
• Mitwirkende: Dinu, Jonathan [MitwirkendeR]
• Institutionen: Pearson (Firm), [Verlag]
• Ausgabe: [First edition].
• Verlagsort: [Place of publication not identified]
• Verlag: Pearson
• E-Jahr: 2024
• Jahr: [2024]
• Umfang: 1 online resource (1 video file (18 hr., 17 min.))
• Illustrationen: sound, color.
• Fussnoten: Online resource; title from title details screen (O’Reilly, viewed October 28, 2024)
• ISBN: 978-0-13-538109-0
• ISBN: 0-13-538109-6
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Intelligence artificielle ; Logiciels
• Sach-SW: Programmation (Informatique)
• Sach-SW: Intelligence artificielle
• Sach-SW: computer programming
• Sach-SW: artificial intelligence
• Sach-SW: Instructional films
• Sach-SW: Nonfiction films
• Sach-SW: Internet videos
• Sach-SW: Films de formation
• Sach-SW: Films autres que de fiction
• Sach-SW: Vidéos sur Internet
• K10plus-PPN: 1910507768
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4629551298
• Lokale URL Inst.: Zum Volltext

Abstract

Programming Generative AI is a hands-on tour of deep generative modeling, taking you from building simple feedforward neural networks in PyTorch all the way to working with large multimodal models capable of simultaneously understanding text and images. Along the way, you will learn how to train your own generative models from scratch to create an infinity of images, generate text with large language models similar to the ones that power applications like ChatGPT, write your own text-to-image pipeline to understand how prompt- based generative models actually work, and personalize large pretrained models like stable diffusion to generate images of novel subjects in unique visual styles (among other things).