Subject Syllabus
AD-802 (A) - Natural Language Processing
AIDS · Semester 8
Course Modules
Learn topic-wise with Hyper AI and revise using mapped PYQs.
in various domainsChallenges and limitations.NLP tasks in syntax, semantics, and pragmatics.Different Data Models such as Boolean ModelVector modelProbabilistic Model.Comparison of classical NLP models: Rule-based modelStatistical modelInformation retrieval modelRule-based machine translation modelProbabilistic Graphical model.
Logics.Syntax-Driven Semantic analysisSemantic attachments.Word SensesRelations between SensesThematic Roles, selectional restrictions.Word-sense disambiguation(WSD): WSD using SupervisedDictionary and Thesaurus.Applications of WSD.TextBooks: 1.Daniel Jurafsky& James H.MartinSpeech and Language ProcessingPerason publication,2018. 2.Steven BirdEwan Klein and Edward LoperNatural Language Processing with PythonFirst EditionOReilly Media, 2009. 3.Nitin Indurkhya-.Handbook of natural language processing.Chapman and Hall/CRC, 2010. 4.Manning and Schutze "Foundations of Statistical Natural Language Processing", MIT Press,2009 ReferenceBooks: 1.Dipanjan Sarkar- Text Analytics with Python.Apress/Springer, 2016 2.RothmanDenis, and Antonio Gulli- Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with PythonPyTorchTensorFlowBERT, and GPT-3.Packt Publishing Ltd, 2022. 3.Tanveer SiddiquiU.S.TiwaryNatural Language Processing and Information RetrievalOxford University Press, 2008