Lecture 16: Dynamic Neural Networks for Question Answering

Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"". Key phrases: Coreference Resolution, Dynamic Memory Networks for Question Answering over Text and Images ------------------------------------------------------------------------------- Natural Language Processing with Deep Learning Instructors: Chris Manning Richard Socher Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component. For additional learning opportunities please visit: http://stanfordonline.stanford.edu/