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#1
September 2nd, 2015, 02:43 PM
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| NLP IIT Kanpur
When the Fourth International Conference on Natural Language Processing at Indian Institutes of Technology IIT Kanpur was conducted? Provide me the list of all members participated in this International Conference?
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#2
February 6th, 2020, 05:15 PM
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| Re: NLP IIT Kanpur
I took admission in IIT Kanpur and searching for details about Natural Language Processing (NLP). Will you tell instructor of NLP IIT Kanpur also provide NLP Course topics to study?
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#3
February 6th, 2020, 05:16 PM
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| Re: NLP IIT Kanpur
Introduction to Natural Language Processing (NLP) Instructor Amitabha Mukerjee Room No. RM507, CSE Dept., Email: amit@cse.iitk.ac.in Lecture Timings and Venue Wed: 10:30 - 11:50 Fri: 10:30 - 11:50 Place: KD101, CSE Department Teaching Assistants M Seetha Ramaiah Email: msram@cse.iitk.ac.in Ayush Mittal Email: ayushmi@cse.iitk.ac.in Girish Kumar Email: girishkr@cse.iitk.ac.in Shivani Tripathi Email: shivtrip@cse.iitk.ac.in NLP Course topics: Course Topics Lecs 1/2 Introduction and Overview : Language Structures and Levels - Sounds / Words / Sentences / Discourse Objectives of NLP Morphological processing Syntactic analysis - parsing. Regular Expressions, demonstrations of use on corpus. Manning / Shuetze: Ch 1 - Rule-based (rationalist) vs probabilistic (empiricist) history Lec 3/4 Morphological processing Rule-based: Porter stemmer Machine-Learning - Unsupervised approaches - HW1 : Unsupervised Morphological Processing / Parallel Corpora [Selection of Papers for Review] NOTE: All Homeworks will be for a non-English language. Lec 5-6 Part of Speech Tagging Supervised Learning / SVM Hidden Markov Models Unsupervised POS tagging [Sub-groups to review Papers on subtopics] Lec 7 Probability and Information Theory ; Naive Bayes models HW2: Spell checker Lecs 8-9 Grammars - CFG grammars - rule-based parsing difficulties. Alternative: Probabilistic grammars Discovering grammars from patterns in text HW3: Unsupervised Syntax discovery [*Special Session: Project Proposal Presentations] [* = extra session] Lec 10-11 Semantic modeling Classical ontology-driven approaches Latent Semantic Analysis Linking Language to Vision / Robotics Lec 12 Word discovery from real situations Aligning unsupervised syntax with sensory structures Lec 13 Machine Translation Acquiring structures from Parallel Corpora Lec 14 Spatial Language and Semantics Lecs 15-19: Interim Project Presentations. Lec END NLP and the rest of AI. Turing test. |
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