Título: Transfer Learning for Natural Language Processing
Autor: Paul Azunre
Sinopse: In Transfer Learning for Natural Language Processing you will learn: Fine tuning pretrained models with new domain data Picking the right model to reduce resource usage Transfer learning for neural network architectures Generating text with generative pretrained transformers Cross-lingual transfer learning with BERT Foundations for exploring NLP academic literature Training deep learning NLP models from scratch is costly, time-consuming, and requires massive amounts of data. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre reveals cutting-edge transfer learning techniques that apply customizable pretrained models to your own NLP architectures. You'll learn how to use transfer learning to deliver state-of-the-art results for language comprehension, even when working with limited label data. Best of all, you'll save on training time and computational costs. Acabamento: Paperback. Peso: 480g. Dimensões: 23.37 x 18.54 x 1.78.
Contexto da obra
Dentro do catálogo, este livro pode ser situado a partir do tema, da autoria e da proposta editorial. “Transfer Learning for Natural Language Processing”, de Paul Azunre, publicado pela editora Manning Publishing, em 2021 e com 272 páginas, integra a categoria Inteligência Artificial. Esse enquadramento pode tornar mais clara a proposta do livro e o tipo de interesse que ele costuma despertar.
Editora: Manning Publishing
Páginas: 272
Ano: 2021
Edição: 1ª EDIÇÃO
Linguagem: Inglês
ISBN:
ISBN13: 9781617297267
