Natural Language Processing 3170723 Syllabus Download With Weightage

Natural Language Processing 3170723 Syllabus Download With Weightage

Natural Language Processing 3170723 is a term that refers to Computer Department covers this subject This year, this Subject is covered in the 7th Semester.   

Sr. No.
1 Introduction to NLP:
What is NLP? Why NLP is Difficult? History of NLP, Advantages of NLP,
Disadvantages of NLP, Components of NLP, Applications of NLP, How to build an NLP
pipeline? Phases of NLP, NLP APIs, NLP Libraries
2 Language Modeling and Part of Speech Tagging:
Unigram Language Model, Bigram, Trigram, N-gram, Advanced smoothing for language
modeling, Empirical Comparison of Smoothing Techniques, Applications of Language
Modeling, Natural Language Generation, Parts of Speech Tagging, Morphology, Named
Entity Recognition
3 Words and Word Forms:
Bag of words, skip-gram, Continuous Bag-Of-Words, Embedding representations for
words Lexical Semantics, Word Sense Disambiguation, Knowledge Based and
Supervised Word Sense Disambiguation
4 Text Analysis, Summarization and Extraction:
Sentiment Mining, Text Classification, Text Summarization, Information Extraction,
Named Entity Recognition, Relation Extraction, Question Answering in Multilingual
Setting; NLP in Information Retrieval, Cross-Lingual IR
5 Machine Translation:
Need of MT, Problems of Machine Translation, MT Approaches, Direct Machine
Translations, Rule-Based Machine Translation, Knowledge Based MT System, Statistical
Machine Translation (SMT), Parameter learning in SMT (IBM models) using EM),
Encoder-decoder architecture, Neural Machine Translation


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