MIT 6.S191: Introduction to Deep Learning - MIT 6.S191: Deep CPCFG for Information Extraction

MIT Introduction to Deep Learning 6.S191: Lecture 9 Deep CPCFG for Information Extraction Lecturer: Nigel Duffy and Freddy Chua, Ernst & Young AI Labs January 2021 For all lectures, slides, and lab materials: http://introtodeeplearning.com​ More details on Deep Conditional Probabilistic Context Free Grammars (CPCFG): https://arxiv.org/abs/2103.05908 Code and datasets: https://github.com/deepcpcfg/datasets Lecture Outline 0:00​ - Introduction 4:18 - What is information extraction? 7:19 - Types of information (headers, line items, etc) 11:57 - Representing document schemas 12:35 - Philosophy of end-to-end deep learning 16:38 - Context free grammars (CFG) 20:55 - Parsing with deep learning 27:10 - Learning objective and training 28:21 - 2 dimensional parsing 33:20 - Handling noise in the parsing 35:23 - Experimental results 38:00 - Question and answering Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!