Natural Language Processing (NLP)

A thorough introduction to cutting-edge technologies applied to Natural Language Processing.

Created by: Xiaodong He

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Course Description

Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence.
In this course, you will be given a thorough overviewof Natural Language Processing and how to use classic machine learning methods. You will learn about Statistical Machine Translation as well as Deep Semantic Similarity Models (DSSM) and their applications.
We will also discuss deep reinforcement learning techniques applied in NLP andVision-Language Multimodal Intelligence.
edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.
Module 1: Introduction to NLP and Deep Learning
An overview of Natural Language Processing using classic machine learning methods and cutting-edge deep learning methods.
Module 2: Neural models for machine translation and conversation
Introduction to Statistical Machine Translation and neural models for translation and conversation
Module 3: Deep Semantic Similarity Models (DSSM)
Introduction to Deep Semantic Similarity Model (DSSM) and its applications.
Module 4: Natural Language Understanding
Introduction to methods applied in Natural Language Understanding, such as continuous word representations and neural knowledge base embedding.
Module 5: Deep reinforcement learning in NLP
Introduction to deep reinforcement learning techniques applied in NLP
Module 6: Vision-Language Multimodal Intelligence
Introduction to neural models applied in Image captioning and visual question answering

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Instructor Details

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Xiaodong He is a Principal Researcher in the Deep Learning Technology Center of Microsoft Research AI, Redmond, WA, USA. He is also an Affiliate Professor in the Department of Electrical Engineering at the University of Washington (Seattle), serves in doctoral supervisory committees. His research interests are mainly in artificial intelligence areas including deep learning, natural language processing, computer vision, speech, information retrieval (IR), and knowledge representation. He has published more than 100 papers in ACL, EMNLP, NAACL, CVPR, SIGIR, WWW, CIKM, NIPS, ICLR, ICASSP, Proc. IEEE, IEEE TASLP, IEEE SPM, and other venues. He received several awards including the Outstanding Paper Award at ACL 2015. He and colleagues invented the DSSM which is broadly applied to language, vision, IR and knowledge representation tasks. He has led the development of the MSR-NRC-SRI entry and the MSR entry that won the No. 1 Place in the 2008 NIST Machine Translation Evaluation and the 2011 IWSLT Evaluation (Chinese-to-English), respectively. He and colleagues also won the first prize, tied with Google, at the COCO Captioning Challenge 2015, and won the first prize at the Visual Question Answering (VQA) Challenge 2017. His work was reported by Communications of the ACM in January 2016. He is leading the image captioning effort now is part of Microsoft Cognitive Services, which provides the world's first image-captioning cloud service, and enables next-generation scenarios such as C

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