Machine Reading Comprehension

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

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• Inteligência artificial

?Attention; Attention mechanism; BERT; Batch generator; BiDAF; CoVe; Commercialization; Contextual embedding; Customer service; Decoder; Deep learning; ELMo; ET-RR; Education; Encoder; Encoding layer; Finance; FusionNet; GPT; Health care; Human parity; Interaction layer; Language model; Laws; Machine reading comprehension; Named entity recognition; Natural language generation; Natural language processing; Natural language understanding; Output layer; Padding; Part-of-speech tagging; Preprocessing; Pretrained language model; R-net; SDNet; Search engine; Tokenization; Transformer; Word vector