Harsh RB

IV Mid 1

6 min read

Deep Learning

Important Questions

Unit 1: 2, 4, 6, 10 Unit 2: 1, 3, 5, 7, 8, 9, 11, 12, 13

  1. Analyze Parameter Tying and Parameter Sharing, Sparse Representations, Bagging and Other Ensemble Methods,
  2. analyzing the Bias and Variance, Maximum Likelihood Estimation, Bayesian Statistics.
  3. applying the Challenges in Neural Network Optimization, Basic Algorithms
  4. create the Deep Feedforward Networks Learning XOR, and Gradient-Based Learning
  5. Evaluate Bagging and Other Ensemble Methods, Dropout, Adversarial Training,
  6. Evaluate the Stochastic Gradient Descent, Building a Machine Learning Algorithm,
  7. Optimization for Training Deep Models, Challenges in Neural Network Optimization,
  8. Remember and explain Parameter Norm Penalties, Norm Penalties as Constrained Optimization,
  9. Remember the Dataset Augmentation, Noise Robustness and Tangent Distance, Tangent Prop, and Manifold Tangent Classifier
  10. Remember the terms of Overfitting and Underfitting and bias and Variance
  11. remembering the Optimization for Training Deep Models, Learning vs Pure Optimization
  12. Understand the Regularization and Under- Constrained Problems, write an Multi- Task Learning with an example
  13. Understanding Regularization and Under-Constrained Problems, Dataset Augmentation,

Assignment questions are in highlighted

NIC

NIC Assignment

Important Questions

Unit 1: 1, 6, 8, 12 Unit 2: 2, 4, 5, 7, 9, 11, 13, 15 Unit 3: 3, 14

  1. Explain hill climbing algorithm with suitable example
  2. Explain basic integrated and fire neuron model
  3. Explain Ant Colony Optimization
  4. Explain network architecture
  5. Explain nuero computing with its scope
  6. Discuss Genetic algorithm steps with example
  7. Demonstrate Artificial Neural Networks
  8. Explain Simulated Annealing algorithm
  9. Explain Mcculloch and pitts model
  10. Explain ANN algorithm
  11. Discuss the Recurrent networks
  12. What is mean by evolutionary computing? explain scope of evolutionary computing
  13. Discuss the nervous system with scope of neurocomputing
  14. Explain algorithm steps involved in Ant Colony Optimization
  15. Explain generic neurocomputing model

Assignment questions are in highlighted

DM

Assignment Questions

Unit 1: 2, 3 Unit 2: 4, 6 Unit 3: 5

1List and explain about various types of OLAP operations in   multidimensional data model
2What is the need of data preprocessing? Discuss briefly about various forms of Data preprocessing techniques
3What is data mining? What are the major issues of data mining? Explain few applications of data mining
4What is apriori property & what is its purpose? Explain join & prune step in apriori algorithm. Disadvantages of apriori algorithms.
5Define Decision tree? Explain how it works for classification problem
6Explain FP growth algorithm? How FP growth algorithm overcomes    limitations of apriori algorithm

Unit 1: 1, 2, 3, 7, 8, 9 Unit 2: 4, 5, 6, 10, 11, 12

1What is data mining? What are the major issues of data mining? Explain few applications of data mining
2List and explain about various types of OLAP operations, in multi-dimensional data model
3a) Explain dimensionality reduction in detail.?
b) How to handle missing values in data sets?
4What is apriori property & what is its purpose? Explain join & prune step in apriori algorithm. Disadvantages of apriori algorithms
5Explain mining in Multilevel Association rules from Transaction databases?
6Apply FP-growth algorithm on the following database to find all of the strong association rules with min_sup = 60% and min_conf = 80%.

7. What is the need of data preprocessing? Discuss briefly about various forms of Data preprocessing techniques
8. List the steps of the Knowledge Discovery in Databases (KDD) and describe each of them.
9. What is missing data? Explain how it is handled. Discuss the issues to be considered during data integration.
10. Explain market basket analysis and its relevance to association rule
11. Explain FP growth algorithm? How FP growth algorithm overcomes    limitations of apriori algorithm
12. Discuss the importance of Association Rule Mining. Explain about confidence and support measures.
13. List out the operations of OLAP. [

b) What is fact table? Write its uses.

c) Define discretization.

 d) What is predictive mining? Explain it briefly.

e) Write the purpose of Apriori algorithm.

f) Define support and confidence measure.

 g) What is boosting?

h) Define decision tree.

 i) Write the strengths of hierarchical clustering.

 j) Compare agglomerative and divisive methods
14. How are association rules generated from frequent itemsets? Illustrate. Explain the procedure to mining closed frequent data item sets.
15. List and describe the Five primitives for specifying a Data Mining Task. b) What are the steps involved in Performing Data Cleaning as a Process?

SW

Important Questions

Unit 1: 1, 7 Unit 2: 2, 3, 4, 6, 8, 10, 11, 12 Unit 3: 5, 9

  1. Discuss the business case for the semantic web with examples?
  2. Describe soap and its role in web services?
  3. Discuss the importance of security in web services in detail?
  4. How to grid enabled service contribute to semantic web?
  5. Explain the structure and components of RDF?
  6. Explain the concept of orchestration in the semantic web?
  7. What is XML and Its Impact on the Enterprise?
  8. what is UDDI and explain its architecture briefly?
  9. Discuss how RDF Capture Knowledge and advantages in semantic web?
  10. What are the Uses, Basics of Web Services and web of web services in semantic web?
  11. Explain about securing of web services.
  12. Explain SOAP and orchestrating web services in semantic web?

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PPLE

Unit 1: 1, 2, 7, 8 Unit 2: 3, 4, 5, 9, 10, 11 Unit 3: 6 Unit 4: 12

  1. Write short notes on the following:
       a) Professional ethics
       b) Personal ethics
       c) Engineering ethics

  2. What is GST in India? Explain the roles and responsibilities of stakeholders of GST.

  3. Write notes with suitable examples on:
       a) Contract of agency
       b) Contract of Guarantee

  4. Explain the essential elements of a valid contract.

  5. Describe the following with appropriate examples:
       a) Unlawful & Illegal contracts
       b) Contingent contract

  6. Explain the following:
       a) Arbitration
       b) Conciliation

  7. Define the following:
       a) Vigil Mechanism
       b) Whistle blowing
       c) Environmental breaches

  8. What are the powers & responsibilities of GST council?

  9. Explain the following with suitable examples:
       a) Contract of Integrity
       b) Contract of Guarantee

  10. Explain different types of discharge of contract.

  11. Explain the different remedies for breach of contract.

  12. Write brief notes on:
       a) Conciliation
       b) Alternative Dispute Resolution System

ES

Assignment Questions

Unit 1: 1, 2, 3 Unit 2: 4, 5, 6 Unit 3: 7, 8, 9

  1. Briefly define and explain all the static and dynamic characteristics of transducers?
  2. What is a strain gauge? Explain the operation of Strain gauge.
  3. Define the sensitivity and linearity of sensor and also write the equations for both.
  4. What is the principle of gas thermometric sensors? Briefly explain about gas thermometric sensors.
  5. What is a Thermometer? Name different types of Thermometers and explain the working principle of all types of Thermometer in detail.
  6. Discuss about the Dielectric Constant and Refractive Index of thermo sensors
  7. Explain the principle of operation of an isotropic magneto resistive(AMR)sensors
  8. Define Hall Effect, draw and explain the Hall Effect sensor.
  9. Explain the principle of operation of Eddy Current Sensors. Also, state its advantages and disadvantage.

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