商品簡介
Take a problem-solving approach to learning all about transformers and get up and running in no time by implementing methodologies that will build the future of NLP
Key Features:
- Explore quick prototyping with up-to-date Python libraries to create effective solutions to industrial problems
- Solve advanced NLP problems such as named-entity recognition, information extraction, language generation, and conversational AI
- Monitor your model's performance with the help of BertViz, exBERT, and TensorBoard
Book Description:
Transformer-based language models have dominated natural language processing (NLP) studies and have now become a new paradigm. With this book, you'll learn how to build various transformer-based NLP applications using the Python Transformers library.
The book gives you an introduction to Transformers by showing you how to write your first hello-world program. You'll then learn how a tokenizer works and how to train your own tokenizer. As you advance, you'll explore the architecture of autoencoding models, such as BERT, and autoregressive models, such as GPT. You'll see how to train and fine-tune models for a variety of natural language understanding (NLU) and natural language generation (NLG) problems, including text classification, token classification, and text representation. This book also helps you to learn efficient models for challenging problems, such as long-context NLP tasks with limited computational capacity. You'll also work with multilingual and cross-lingual problems, optimize models by monitoring their performance, and discover how to deconstruct these models for interpretability and explainability. Finally, you'll be able to deploy your transformer models in a production environment.
By the end of this NLP book, you'll have learned how to use Transformers to solve advanced NLP problems using advanced models.
What You Will Learn:
- Explore state-of-the-art NLP solutions with the Transformers library
- Train a language model in any language with any transformer architecture
- Fine-tune a pre-trained language model to perform several downstream tasks
- Select the right framework for the training, evaluation, and production of an end-to-end solution
- Get hands-on experience in using TensorBoard and Weights & Biases
- Visualize the internal representation of transformer models for interpretability
Who this book is for:
This book is for deep learning researchers, hands-on NLP practitioners, as well as ML/NLP educators and students who want to start their journey with Transformers. Beginner-level machine learning knowledge and a good command of Python will help you get the best out of this book.
購物須知
外文書商品之書封，為出版社提供之樣本。實際出貨商品，以出版社所提供之現有版本為主。部份書籍，因出版社供應狀況特殊，匯率將依實際狀況做調整。
無庫存之商品，在您完成訂單程序之後，將以空運的方式為你下單調貨。為了縮短等待的時間，建議您將外文書與其他商品分開下單，以獲得最快的取貨速度，平均調貨時間為1~2個月。
為了保護您的權益，「三民網路書店」提供會員七日商品鑑賞期(收到商品為起始日)。
若要辦理退貨，請在商品鑑賞期內寄回，且商品必須是全新狀態與完整包裝(商品、附件、發票、隨貨贈品等)否則恕不接受退貨。