{"product_id":"hands-on-question-answering-systems-with-bert-applications-in-neural-networks-and-natural-language-processing-paperback","title":"Hands-On Question Answering Systems with Bert: Applications in Neural Networks and Natural Language Processing - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eNavin Sabharwal\u003c\/b\u003e (Author), \u003cb\u003eAmit Agrawal\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eGet 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.\u003c\/p\u003e \u003cp\u003eThe 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. \u003c\/p\u003e \u003cp\u003eAfter 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. \u003c\/p\u003e \u003cp\u003eHands-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.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eWhat You Will Learn\u003c\/b\u003e\u003c\/p\u003e \u003cli\u003eExamine the fundamentals of word embeddings\u003c\/li\u003e \u003cli\u003eApply neural networks and BERT for various NLP tasks\u003c\/li\u003e Develop a question-answering system from scratch \u003cli\u003eTrain question-answering systems for your own data\u003c\/li\u003e  \u003cp\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAI and machine learning developers and natural language processing developers.\u003c\/p\u003e\u003cbr\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eGet 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.\u003c\/p\u003e\u003cp\u003eThe 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.\u003c\/p\u003e\u003cp\u003eAfter 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.\u003c\/p\u003e\u003cp\u003e\u003ci\u003eHands-on Question Answering Systems with BERT\u003c\/i\u003e 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.\u003c\/p\u003e\u003cp\u003eYou will: \u003cb\u003e\u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eExamine the fundamentals of word embeddings\u003c\/li\u003e\n\u003cli\u003eApply neural networks and BERT for various NLP tasks\u003c\/li\u003e\n\u003cli\u003eDevelop a question-answering system from scratch\u003c\/li\u003e\n\u003cli\u003eTrain question-answering systems for your own data\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eNavin is the chief architect for HCL DryICE Autonomics. He is an innovator, thought leader, author, and consultant in the areas of AI, machine learning, cloud computing, big data analytics, and software product development. He is responsible for IP development and service delivery in the areas of AI and machine learning, automation, AIOPS, public cloud GCP, AWS, and Microsoft Azure. Navin has authored 15+ books in the areas of cloud computing, cognitive virtual agents, IBM Watson, GCP, containers, and microservices. \u003c\/p\u003e Amit Agrawal is a senior data scientist and researcher delivering solutions in the fields of AI and machine learning. He is responsible for designing end-to-end solutions and architecture for enterprise products. He has also authored and reviewed books in the area of cognitive virtual assistants. \u003cp\u003e\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 184\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.43 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e January 13, 2021\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":52493574013235,"sku":"9781484266632","price":55.58,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/OC9IYmJvR3EwQXNwMVplZVpoL2V1QT09.webp?v=1759957143","url":"https:\/\/www.vysn.com\/products\/hands-on-question-answering-systems-with-bert-applications-in-neural-networks-and-natural-language-processing-paperback","provider":"VYSN","version":"1.0","type":"link"}