Standort: ---
Exemplare:
---
| Online-Ressource |
Titel: | Learn generative AI with PyTorch |
Mitwirkende: | Liu, Mark [VerfasserIn]  |
Institutionen: | Manning Publications (Firm), [Verlag]  |
Verf.angabe: | Mark Liu |
Ausgabe: | [First edition]. |
Verlagsort: | [Shelter Island, New York] |
Verlag: | Manning Publications |
E-Jahr: | 2025 |
Jahr: | [2025] |
Umfang: | 1 online resource (1 video file (12 hr., 58 min.)) |
Illustrationen: | sound, color. |
Fussnoten: | "In video editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.". - Online resource; title from title details screen (O’Reilly, viewed February 17, 2025) |
Abstract: | Learn Generative AI with PyTorch introduces the underlying mechanics of generative AI by helping you build your own working AI models. You’ll begin by creating simple images using a GAN, and then progress to writing a language translation transformer line-by-line. As you work through the fun and fascinating projects, you’ll train models to create anime images, write like Hemingway, make music like Mozart, and more. You just need Python and a few machine learning basics to get started. You’ll learn the rest as you go! |
URL: | Aggregator: https://learning.oreilly.com/library/view/-/9781633436466VE/?ar |
Datenträger: | Online-Ressource |
Sprache: | eng |
Sach-SW: | Intelligence artificielle |
| Apprentissage automatique |
| Python (Langage de programmation) |
| artificial intelligence |
Form-SW: | Instructional films |
| Nonfiction films |
| Internet videos |
| Films de formation |
| Films autres que de fiction |
| Vidéos sur Internet |
K10plus-PPN: | 1919256865 |
|
|
| |
Lokale URL UB: | Zum Volltext |
|
|
| Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg |
| Bestellen/Vormerken für Benutzer des Klinikums Mannheim Eigene Kennung erforderlich |
Bibliothek/Idn: | UW / m4683427141 |
Lokale URL Inst.: | Zum Volltext |
Learn generative AI with PyTorch / Liu, Mark [VerfasserIn]; [2025] (Online-Ressource)
69315691