Mastering Transformers: Build state-of-the-art models from scratch with advanced natural language processing techniques (Paperback)
暫譯: 掌握變壓器:從零開始構建最先進的模型,運用高級自然語言處理技術 (平裝本)

Yıldırım, Savaş, Asgari-Chenaghlu, Meysam

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商品描述

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.

商品描述(中文翻譯)

採用問題解決的方法來學習變壓器,並通過實施將構建 NLP 未來的方法論,迅速上手

主要特點:


  • 探索使用最新的 Python 函式庫進行快速原型設計,以創造有效的工業問題解決方案

  • 解決高級 NLP 問題,如命名實體識別、信息提取、語言生成和對話式 AI

  • 利用 BertViz、exBERT 和 TensorBoard 監控模型的性能

書籍描述:

基於變壓器的語言模型已主導自然語言處理 (NLP) 研究,並已成為一種新的範式。在這本書中,您將學習如何使用 Python Transformers 函式庫構建各種基於變壓器的 NLP 應用程序。

這本書通過展示如何編寫您的第一個 hello-world 程式來介紹變壓器。接著,您將學習分詞器的工作原理以及如何訓練自己的分詞器。隨著進步,您將探索自編碼模型的架構,例如 BERT,以及自回歸模型,例如 GPT。您將看到如何訓練和微調模型以解決各種自然語言理解 (NLU) 和自然語言生成 (NLG) 問題,包括文本分類、標記分類和文本表示。這本書還幫助您學習針對挑戰性問題(例如具有有限計算能力的長上下文 NLP 任務)的高效模型。您還將處理多語言和跨語言問題,通過監控模型性能來優化模型,並發現如何解構這些模型以提高可解釋性和可解釋性。最後,您將能夠在生產環境中部署您的變壓器模型。

在這本 NLP 書籍結束時,您將學會如何使用變壓器來解決高級 NLP 問題,並使用先進模型。

您將學到的內容:


  • 探索使用 Transformers 函式庫的最先進 NLP 解決方案

  • 使用任何變壓器架構訓練任何語言的語言模型

  • 微調預訓練的語言模型以執行多個下游任務

  • 為端到端解決方案的訓練、評估和生產選擇合適的框架

  • 獲得使用 TensorBoard 和 Weights & Biases 的實踐經驗

  • 可視化變壓器模型的內部表示以提高可解釋性

本書適合誰:

這本書適合深度學習研究人員、實踐 NLP 的專業人士,以及希望開始變壓器之旅的 ML/NLP 教育工作者和學生。具備初級機器學習知識和良好的 Python 基礎將幫助您充分利用這本書。