{"id":18709,"date":"2020-09-11T15:13:05","date_gmt":"2020-09-11T15:13:05","guid":{"rendered":"https:\/\/www.inspirenignite.com\/mh\/it703de-01-natural-language-processing-syllabus-for-it-7th-sem-2020-21-dbatu-elective-viii\/"},"modified":"2020-09-11T15:13:05","modified_gmt":"2020-09-11T15:13:05","slug":"it703de-01-natural-language-processing-syllabus-for-it-7th-sem-2020-21-dbatu-elective-viii","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/mh\/it703de-01-natural-language-processing-syllabus-for-it-7th-sem-2020-21-dbatu-elective-viii\/","title":{"rendered":"IT703DE-01: Natural Language Processing Syllabus for IT 7th Sem 2020-21 DBATU (Elective-VIII)"},"content":{"rendered":"

Natural Language Processing detailed syllabus scheme for Information Technology (IT), 2020-21 onwards has been taken from the DBATU<\/a> official website and presented for the Bachelor of Technology students. For Subject Code, Course Title, Lecutres, Tutorials, Practice, Credits, and other information, do visit full semester subjects post given below. <\/p>\n

For 7th Sem Scheme of Information Technology (IT), 2020-21 Onwards, do visit IT 7th Sem Scheme, 2020-21 Onwards<\/a>. For the Elective-VIII scheme of 7th Sem 2020-21 onwards, refer to IT 7th Sem Elective-VIII Scheme 2020-21 Onwards<\/a>. The detail syllabus for natural language processing is as follows.<\/p>\n

Natural Language Processing Syllabus for Information Technology (IT) 4th Year 7th Sem 2020-21 DBATU<\/h2>\n

Natural Language Processing<\/title><\/p>\n<h4>Course Objectives:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier.<\/b><br \/><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Course Outcomes:<\/h4>\n<p> After learning the course the student will be able:<\/p>\n<ol>\n<li>To understand the models, methods, and algorithms of statistical Natural Language Processing<\/li>\n<li>To implement probabilistic models in code, estimate parameters for such models, and run meaningful experiments to validate such models.<\/li>\n<li>To apply core computer science concepts and algorithms, such as dynamic programming.<\/li>\n<li>To understand linguistic phenomena and explore the linguistic features relevant to each NLP task.<\/li>\n<li>To identify opportunities and conduct research in NLP<\/li>\n<li>To analyze experimental results and write reports<\/li>\n<\/ol>\n<h4>Unit I<\/h4>\n<p> introduction to NLP: Definition, issues and strategies, application domain, tools for NLP, Linguistic organization of NLP, NLP vs PLP.<\/p>\n<h4>Unit II<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier.<\/b><br \/><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Unit III<\/h4>\n<p> Phonology: Speech sounds, phonetic transcription, phoneme and phonological rules, optimality theory, machine learning of phonological rules, phonological aspects of prosody and speech synthesis. Pronunciation, Spelling and N-grams: Spelling errors, detection and elimination using probabilistic models, pronunciation variation (lexical, allophonic, dialect), decision tree model, counting words in Corpora, simple N-grams, smoothing (Add one, Written-Bell, Good-Turing), N-grams for spelling and pronunciation.<\/p>\n<h4>Unit IV<\/h4>\n<p> Syntax: POS Tagging: Tagsets, concept of HMM tagger, rule based and stochastic POST, algorithm for HMM tagging, transformation based tagging. Sentence level construction and unification: Noun phrase, co-ordination, sub-categorization, concept of feature structure and unification.<\/p>\n<h4>Unit V<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier.<\/b><br \/><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Unit VI<\/h4>\n<p> Pragmatics: Discourse: Reference resolution and phenomena, syntactic and semantic constraints on coreference, pronoun resolution algorithm, text coherence, discourse structure. Dialogues: Turns and utterances, grounding, dialogue acts and structures. Natural Language Generation: Introduction to language generation, architecture, discourse planning (text schemata, rhetorical relations)<\/p>\n<h4>Text Books:<\/h4>\n<ol>\n<li>D. Jurafsky and J. H. Martin – Speech and Language Processing – An introduction to Language processing, Computational Linguistics, and Speech Recognition, Pearson Education<\/li>\n<li>Allen, James. 1995. – Natural Language Understanding. Benjamin\/Cummings, 2ed.<\/li>\n<\/ol>\n<h4>Reference Book:<\/h4>\n<ol>\n<li>Bharathi, A., Vineet Chaitanya and Rajeev Sangal. 1995. Natural Language Processing-A Pananian Perspective. Prentice Hall India, Eastern Economy Edition.<\/li>\n<li>Eugene Cherniak, Statistical Language Learning, MIT Press, 1993.<\/li>\n<li>Manning, Christopher and Heinrich Schutze, Foundations of Statistical Natural Language Processing. MIT Press, 1999.<\/li>\n<\/ol>\n<p align=\"justify\">For detail syllabus of all subjects of Information Technology (IT) 7th Sem 2020-21 onwards, visit <a href=\"..\/category\/dbatu\/7th-sem-dbatu\">IT 7th Sem Subjects <\/a>of 2020-21 Onwards.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Natural Language Processing detailed syllabus scheme for Information Technology (IT), 2020-21 onwards has been taken from the DBATU official website and presented for the Bachelor of Technology students. For Subject […]<\/p>\n","protected":false},"author":2351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[109],"tags":[],"class_list":["post-18709","post","type-post","status-publish","format-standard","hentry","category-it-dbatu"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/posts\/18709","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/users\/2351"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/comments?post=18709"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/posts\/18709\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/media?parent=18709"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/categories?post=18709"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/tags?post=18709"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}