Subject1=Social Media Mining

1.Contrast by illustrative figures: Hamiltonian Cycle and Euler circuit

2.Draw a tree and represent its BFS, DFS spanning trees.

3.Write any one shortest path algorithm

4.Elucidate about Small World Model

5.Elucidate about Preferential Attachment Model

6.Contrast with an example for each: Supervised learning Vs. Unsupervised learning

7.Delineate Datamining Algorithms

8.Delineate the following

(a)Centrality Vs. Similarity   (b)Transitivity and Reciprocity 

Subject2=Neural Networks and Deep Learning

1.Delineate the following

(a)Supervised Learning Networks  (b)Perceptron Networks

2.Delineate the following

(a)Back propogation networks  (b)BAM and Hopfield networks

3.Delineate the following

(a)Associative Memory Networks  (b)Regularization and Underconstrained Problems

4.Delineate the following

(a)Bagging and other Ensemble Methods (b)Adversarial Training

5.Delineate the following

(a)Semi-Supervised Learning (b)Multi-Task Learning

6.Delineate the following

(a)Learning Vs. Pure Optimization (b)Challenges in Neural Network Optimization

7.Delineate the following

(a)Dataset augmentation (b)Algorithms with adaptive learning rates

8.Delineate the following

(a)Early Stopping   (b) Paramenter Tying and Parameter Sharing