Natural Language Processing (B.Tech)

Departmental Elective-IV: text processing, language models, parsing, semantics and NLP applications.

6 महीनेअवधि 5Chapters33टॉपिक

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सिलेबस · पाठ्यक्रम

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01Unit 1: Introduction and Language Modelling 7 टॉपिक

Origins and challenges of NLP
Language and grammar
Processing Indian languages
NLP applications and information retrieval
Regular expressions and finite state automata
Morphology, stemming and tokenization
Spelling error detection and minimum edit distance

02Unit 2: Word Level Analysis 7 टॉपिक

Unsmoothed N-grams
Evaluating N-grams: perplexity
Smoothing: Laplace, interpolation and backoff
Word classes and POS tagging
Rule-based and stochastic (HMM) tagging
Viterbi algorithm
Transformation-based (Brill) tagging

03Unit 3: Syntactic Analysis 7 टॉपिक

Context-free grammars
Grammar rules for English and treebanks
Normal forms (CNF)
Top-down and bottom-up parsing
CYK parsing
Probabilistic CFG
Feature structures and unification

04Unit 4: Semantic Analysis 6 टॉपिक

Meaning representation and first order logic
Syntax-driven semantic analysis
Word senses and relations (synonymy, hyponymy)
Thematic roles and selectional restrictions
Word sense disambiguation: supervised, Lesk, bootstrapping
Word similarity: thesaurus and distributional

05Unit 5: Discourse and NLP Applications 6 टॉपिक

Discourse cohesion and coherence
Reference and coreference resolution
Machine translation
Question answering and information extraction
Sentiment analysis and summarization
TF-IDF and word embeddings

परिचय

आप यह कर पाएँगे

Explain the levels of language analysis and challenges of NLP, including Indian languages
Use regular expressions, finite state automata, stemming and minimum edit distance
Build and evaluate N-gram language models with smoothing
Perform POS tagging with rule-based, HMM (Viterbi) and transformation-based methods
Parse sentences with CFG, CYK and probabilistic CFG
Explain semantics, word sense disambiguation and NLP applications such as MT, QA and sentiment analysis

यह किसके लिए है

B.Tech Information Technology students of Semester 7 (AKTU)
Students of other universities studying the same subject who want unit-wise coaching

आपको क्या चाहिए

Basic probability and discrete mathematics
Python programming (NLTK / spaCy useful)

सवाल

Which syllabus does the Natural Language Processing course follow?

It follows the AKTU (Dr. A.P.J. Abdul Kalam Technical University, Lucknow) B.Tech syllabus for Natural Language Processing. If your own university's syllabus differs, the centre follows your university syllabus.

Will this help in the university examination?

Yes. Teaching is unit-wise as per the AKTU scheme, with previous-year question practice, MCQ tests and doubt sessions before the semester exam.

Do we write NLP programs?

Yes. Concepts are shown with small Python programs using NLTK, so you understand N-grams, tagging and parsing practically.