![]() For example, sequence to sequence transformer is covered with application in machine translation. Foundations and advancements in Deep Learning are taught, integrated with NLP problems. Language tasks are examined through the lens of Deep Learning. Students of the course which typically number more than 100, acquire a grip on tasks, techniques and linguistics of a plethora of NLP problems.ĬS772( Deep Learning for Natural Language Processing) comes as a natural sequel to CS626. The course CS626 (Speech, NLP and the Web) being taught in the first semester in CSE Dept IIT Bombay for last several years creates a strong foundation of NLP covering the whole NLP stack starting from morphology to part of speech tagging, to parsing and discourse and pragmatics. ![]() DL has found heavy use in Natural Language Processing (NLP) too, including problems like machine translation, sentiment and emotion analysis, question answering, information extraction and so on, improving performance on automatic systems by order of magnitude. Join the MS Teams using the code 8ht1h3mĬourse Details CS772: Deep Learning for Natural Language Processingĭepartment of Computer Science and Engineering Indian Institute of Technology Bombay Time Table and Venueĭeep Learning (DL) is a framework for solving AI problems based on a network of neurons organized in many layers.CS772: Deep Learning for Natural Language Processing Announcement ![]()
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