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IT-802 (B) · Natural Language Processing/Important Questions

Natural Language Processing (IT-802 (B)) - Important Questions

  1. Unit 37 Marks Medium Priority Asked: 2024

    What do you know about Parsing? Differentiate synthetic and statistical parsers.

    Transcribed from NATURAL LANGUAGE PROCESSING - DEC 2024, Unit 3 question.

  2. Unit 37 Marks Medium Priority Asked: 2025

    Explain the role of activation functions in a multilayer perception. How do they enable the learning of nonlinear patterns?

    Transcribed from A MACHINE LEARNING - JUN 2025, Unit 3 question (activation functions / MLP).

  3. Unit 37 Marks Medium Priority Asked: 2023

    Solve the following problem using linear regression and find how well does the regression equation fit the data? Also find that if a product sold in 40 months, what sales would we expect in statistics?

    Table:

    Product_Name Time (in_months) Sales (in _tons)
    Product_A 48 62
    Product_B 24 30
    Product_C 36 40
    Product_D 60 50
    Product_E 72 70

    Transcribed exactly from A MACHINE LEARNING - MAY 2023, Unit 3 question (regression problem). Table preserved as in original question.

  4. Unit 37 Marks Medium Priority Asked: 2023

    Explain Linear and Logistic regression. What are the advantages for the same?

    Transcribed from A MACHINE LEARNING - MAY 2023, Unit 3 question (regression theory).

  5. Unit 37 Marks Medium Priority Asked: 2023

    What is the objective of convergence of cost function? Can we use it for the linear regression and how it's related to SSE? Justify your answer with proper explanation.

    Transcribed from A MACHINE LEARNING - MAY 2023, Unit 3 question (cost function convergence / SSE).

  6. Unit 37 Marks Medium Priority Asked: 2024

    Describe Part-of-Speech tagging. Discuss the Maximum Entropy model for POS tagging (or other POS methods like TBL).

    Core topic repeatedly seen in Unit 3 past papers and analytics heatmap; exact phrasing from aggregated analytics.

  7. Unit 37 Marks Medium Priority Asked: 2024

    Questions on morphology and its relation to finitestate methods (morphology, FSTs): explain morphology and FST-based analysis.

    Morphology + FST topic appears in analytics and past papers; phrasing preserved from analytics summary.

  8. Unit 37 Marks Medium Priority Asked: 2024

    Discuss any four broad classes / commercial uses of Natural Language Processing (NLP).

    High-frequency conceptual question from analytics summarizing common exam demand on applications of NLP.

  9. Unit 37 Marks Medium Priority Asked: 2024

    Topics on Semantic Analysis (anaphora / named entity resolution / bootstrapping methods / WSD).

    Semantic analysis topics recurring in analytics; preserved wording from aggregated summary.

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