Table of Contents

Part I: Foundation1. Introduction to Machine Reading Comprehension2. The Basics of Natural Language Processing3. Deep Learning in Natural Language Processing

Part II: Architecture4. Architecture of MRC Models5. Common MRC Models6. Pre-trained Language Model

Part III: Application7. Code Analysis of SDNet Model8. Applications and Future of Machine Reading Comprehension

AppendixA. Machine Learning BasicsB. Deep Learning Basics

About the Author

Principal Research Manager in Microsoft Corporation. Dr. Zhu obtained his Ph.D. in Computer Science from Stanford University. He is leading efforts in research and productization of natural language processing in Azure Cognitive AI. Dr. Zhu is proficient in artificial intelligence, deep learning and natural language processing, specializing in machine reading comprehension, text summarization and dialogue understanding. He has led teams to win the first place in the SQuAD 1.0 Machine Reading Comprehension Competition held by Stanford University, and reach human parity in the CoQA Conversational Reading Comprehension Competition. He has 40 papers published in top AI and NLP conferences such as ACL, EMNLP, NAACL and ICLR with more than 1,000 citations.