Hallo! Tracked shipping to Netherlands with Delivery Duty Paid for just €7 

Ship to
Netherlands
0
  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

Select your country

Americas

Europe

Rest of the world

portada Natural Language Processing With Transformers, Revised Edition
Type
Physical Book
Publisher
Year
2022
Language
English
Pages
406
Format
Paperback
Dimensions
23.3 x 17.8 x 2.1 cm
Weight
0.65 kg.
ISBN13
9781098136796
Edition No.
1

Natural Language Processing With Transformers, Revised Edition

Thomas Wolf (Author) · Lewis Tunstall (Author) · Leandro Von Werra (Author) · O'Reilly Media · Paperback

Natural Language Processing With Transformers, Revised Edition - Tunstall, Lewis ; Von Werra, Leandro ; Wolf, Thomas

5 estrellas - de un total de 5 estrellas 1 review
Cheaper New Book Imported to Netherlands
Delivery: 08 Sep - 15 Sep Shipping: 16 to 20 business days.
€ 51,07
Faster New Book Imported to Netherlands
Delivery: 18 Aug - 19 Aug Shipping: 2 to 2 business days.
€ 75,93
Import costs and 9% BTW included in the price ✅
€ 51,07

Synopsis "Natural Language Processing With Transformers, Revised Edition "

Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf, among the creators of Hugging Face Transformers, use a hands-on approach to teach you how transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve. Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering Learn how transformers can be used for cross-lingual transfer learning Apply transformers in real-world scenarios where labeled data is scarce Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization Train transformers from scratch and learn how to scale to multiple GPUs and distributed environments

Customers reviews

Ma Angelica Nates Wednesday, May 22, 2024
Verified Purchase

Excelente, súper claro y practico

00
  • 100% (1)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews