Language:
English
Pages:
1 online resource (1 video file (1 hr., 24 min.))
,
sound, color.
Edition:
Revised edition.
DDC:
006.3/5
Keywords:
Natural language processing (Computer science)
;
Machine learning
;
Cloud computing
;
Traitement automatique des langues naturelles
;
Apprentissage automatique
;
Infonuagique
;
Instructional films
;
Nonfiction films
;
Internet videos
;
Films de formation
;
Films autres que de fiction
;
Vidéos sur Internet
Abstract:
Sponsored by deepset Join us for this edition of O'Reilly Book Club with Lewis Tunstall and Leandro von Werra, authors of Natural Language Processing with Transformers, to learn how transformers, which are the backbone of the state-of-the-art LLM models in the field today, work and how to integrate them in your applications. Bringing insights from their experience working at Hugging Face, Lewis and Leandro will discuss the benefits and challenges of training your own model, scaling, and deploying it for your system. Learn tricks of the trade, listen to stories, and gain new insights. What you'll learn and how you can apply it Learn about a variety of NLP tasks transformers can help you solve Understand how transformers can be used for transfer learning Learn about building, debugging, and optimizing transformer models This live event is for you because... You want to go beyond the words on the page and ask your own questions. You're a data scientist, machine learning engineer, or developer who is working with AI and machine learning and want to learn about the latest developments in the field. Recommended follow-up: Read Natural Language Processing with Transformers, Revised Edition (book) Read Hands-On Large Language Models (early release book) Read Hands-On Generative AI with Transformers and Diffusion Models (early release book) Read Introduction to Transformers for NLP: With the Hugging Face Library and Models to Solve Problems (book) Watch Natural Language Processing Using Transformer Architectures (video).
Note:
Online resource; title from title details screen (O'Reilly, viewed November 1, 2023)
