Transfer Learning for Natural Language Processing (Paperback)
Azunre, Paul
- 出版商: Manning
- 出版日期: 2021-11-03
- 售價: $1,900
- 貴賓價: 9.5 折 $1,805
- 語言: 英文
- 頁數: 250
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1617297267
- ISBN-13: 9781617297267
-
相關分類:
人工智慧、Machine Learning、Text-mining
-
相關翻譯:
自然語言處理遷移學習實戰 (簡中版)
立即出貨 (庫存 < 3)
買這商品的人也買了...
-
電腦網路, 5/e (Computer Networks, 5/e) (授權經銷版)$940$893 -
A Visual Guide to Stata Graphics, 3/e (Paperback)$3,560$3,382 -
$2,928The R Book, 2/e (Hardcover) -
$3,150Applied Predictive Modeling (Hardcover) -
$1,680An Introduction to Statistical Learning: With Applications in R (Hardcover) -
$1,744Time Series Analysis: Forecasting and Control, 5/e (Hardcover) -
Deep Learning 深度學習基礎｜設計下一代人工智慧演算法 (Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms)$620$490 -
學會 TensorFlow 之後呢？最尖端的 21個夢幻範例實作$680$578 -
初探深度學習｜使用 TensorFlow (TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning)$480$379 -
Probabilistic Machine Learning: An Introduction (Hardcover)$2,650$2,597 -
Deep Generative Modeling$3,370$3,202 -
Bayesian Optimization in Action (Paperback)$2,300$2,185
相關主題
商品描述
Transfer Learning for Natural Language Processing gets you up to speed with the relevant ML concepts before diving into the cutting-edge advances that are defining the future of NLP.
Building and training deep learning models from scratch is costly, time-consuming, and requires massive amounts of data. To address this concern, cutting-edge transfer learning techniques enable you to start with pretrained models you can tweak to meet your exact needs. In Transfer Learning for Natural Language Processing, you'll go hands-on with customizing these open source resources for your own NLP architectures.
Transfer Learning for Natural Language Processing gets you up to speed with the relevant ML concepts before diving into the cutting-edge advances that are defining the future of NLP. You'll learn how to adapt existing state-of-the art models into real-world applications, including building a spam email classifier, a movie review sentiment analyzer, an automated fact checker, a question-answering system and a translation system for low-resource languages.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
商品描述(中文翻譯)
《自然語言處理的遷移學習》將帶您深入了解相關的機器學習概念，然後再深入探討正在定義自然語言處理未來的尖端進展。建立和訓練深度學習模型需要大量成本、時間和數據。為了解決這個問題，尖端的遷移學習技術使您能夠從預訓練模型開始，並根據自己的需求進行調整。在《自然語言處理的遷移學習》中，您將親自動手將這些開源資源定制為自己的自然語言處理架構。《自然語言處理的遷移學習》將帶您深入了解相關的機器學習概念，然後再深入探討正在定義自然語言處理未來的尖端進展。您將學習如何將現有的最先進模型適應到現實應用中，包括構建垃圾郵件分類器、電影評論情感分析器、自動事實檢查器、問答系統和低資源語言的翻譯系統。購買印刷版書籍將包含一本免費的PDF、Kindle和ePub格式的電子書，由Manning Publications提供。
作者簡介
Paul Azunre holds a PhD in Computer Science from MIT and has served as a Principal Investigator on several DARPA research programs. He founded Algorine Inc., a Research Lab dedicated to advancing AI/ML and identifying scenarios where they can have a significant social impact. Paul also co-founded Ghana NLP, an open source initiative focused using NLP and Transfer Learning with Ghanaian and other low-resource languages. He frequently contributes to major peer-reviewed international research journals and serves as a program committee member at top conferences in the field.
作者簡介(中文翻譯)
Paul Azunre擁有麻省理工學院的計算機科學博士學位，並曾擔任多個DARPA研究計劃的首席調查員。他創辦了Algorine Inc.，一個致力於推進人工智能/機器學習並確定其對社會產生重大影響的研究實驗室。Paul還共同創辦了Ghana NLP，這是一個開源倡議，專注於使用自然語言處理和轉移學習來處理迦納和其他資源有限的語言。他經常在主要的同行評審國際研究期刊上發表論文，並擔任該領域頂級會議的程序委員會成員。
