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Hands-On Question Answering Systems with Bert

Hands-On Question Answering Systems with Bert


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About the Book

Chapter 1: Introduction to Natural Language ProcessingChapter Goal: To introduce basics of natural language processing1.1 What is natural language processing1.2 What is natural language understanding1.3 Natural language processing tasks1.3.1 Tokenization1.3.2 Stemming and lemmatization1.3.3 Bag of words1.3.4 Word / Sentence vectorization
Chapter 2: Introduction to Word Embeddings
Chapter Goal: To introduce the basics of word embeddings3.1 What is word embeddings3.2 Different methods of word embeddings3.2.1 Word2vec3.2.2 Glove3.2.3 Elmo3.2.4 Universal sentence encoders3.2.5 BERT3.3 Bidirectional Encoder Representations from Transformers (BERT)3.3.1 BERT - base3.3.2 BERT - large
Chapter 3: BERT Algorithms ExplainedChapter Goal: Details on BERT model algorithms4.1 Masked language model4.2 Next sentence prediction (NSP) 4.3 Text classification using BERT4.4 Various types of BERT based models4.4.1 ALBERT4.4.2 ROBERT4.4.3 DistilBERT
Chapter 4: BERT Model Applications - Question Answering SystemChapter Goal: Details on question answering system5.1 Introduction5.2 Types of QA systems5.3 QA system design using BERT5.4 DrQA system5.5 DeepPavlov QA system
Chapter 5: BERT Model Applications - Other tasksChapter Goal: Details on NLP tasks performed by BERT.6.1 Introduction6.2 Other NLP Tasks: 6.2.1 Sentiment analysis 6.2.2. Named entity recognition 6.2.3 Tag generation 6.2.4 Classification 6.2.5 Text summarization 6.2.6 Language translation
Chapter 6: Future of BERT modelsChapter Goal: Provides an introduction to the new advances in the areas NLP using BERT7.1 BERT - Future capabilities


About the Author:

Navin 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.

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.


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Product Details
  • ISBN-13: 9781484266632
  • Publisher: Apress
  • Publisher Imprint: Apress
  • Height: 234 mm
  • No of Pages: 184
  • Spine Width: 11 mm
  • Weight: 340 gr
  • ISBN-10: 1484266633
  • Publisher Date: 13 Jan 2021
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Sub Title: Applications in Neural Networks and Natural Language Processing
  • Width: 156 mm


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