| 書目名稱 | Hands-on Question Answering Systems with BERT | | 副標(biāo)題 | Applications in Neur | | 編輯 | Navin Sabharwal,Amit Agrawal | | 視頻video | http://file.papertrans.cn/424/423992/423992.mp4 | | 概述 | Integrates question answering systems with document repositories from different sources.Contains an in-depth explanation of the technology behind BERT.Takes a step-by-step approach to building questio | | 圖書封面 |  | | 描述 | .Get hands-on knowledge of how BERT (Bidirectional Encoder Representations from Transformers) can be used to develop question answering (QA) systems by using natural language processing (NLP) and deep learning...The book begins with an overview of the technology landscape behind BERT. It takes you through the basics of NLP, including natural language understanding with tokenization, stemming, and lemmatization, and bag of words. Next, you’ll look at neural networks for NLP starting with its variants such as recurrent neural networks, encoders and decoders, bi-directional encoders and decoders, and transformer models. Along the way, you’ll cover word embedding and their types along with the basics of BERT. ..After this solid foundation, you’ll be ready to take a deep dive into BERT algorithms such as masked language models and next sentence prediction. You’ll see different BERT variations followed by a hands-on example of a question answering system. ..Hands-on Question Answering Systems with BERT is a good starting point for developers and data scientists who want to develop and design NLP systems using BERT. It provides step-by-step guidance for using BERT...What You Will Learn..E | | 出版日期 | Book 2021 | | 關(guān)鍵詞 | Natural Language Processing; BERT; Natural Language Understanding; Encoders; Bi Dorectional Encoders; Wor | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-6664-9 | | isbn_softcover | 978-1-4842-6663-2 | | isbn_ebook | 978-1-4842-6664-9 | | copyright | Navin Sabharwal, Amit Agrawal 2021 |
The information of publication is updating
|
|
|Archiver|手機(jī)版|小黑屋|
派博傳思國際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-10-11 10:55
發(fā)表于 2025-3-21 17:54:43
