What does the Bayesian network provides? a) Complete description of the domain b) Partial description of the domain c) Complete description of the problem d) None of the mentioned
1 6690Fuzzy logic is usually represented as a) IF-THEN-ELSE rules b) IF-THEN rules c) Both a & b d) None of the mentioned
1 6035______________ is/are the way/s to represent uncertainty. a) Fuzzy Logic b) Probability c) Entropy d) All of the mentioned
4110____________ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned
3351Which condition is used to influence a variable directly by all the others? a) Partially connected b) Fully connected c) Local connected d) None of the mentioned
1774What is the consequence between a node and its predecessors while creating Bayesian network? a) Conditionally dependent b) Dependent c) Conditionally independent d) Both a & b
2555A 3-input neuron is trained to output a zero when the input is 110 and a one when the input is 111. After generalization, the output will be zero when and only when the input is: a) 000 or 110 or 011 or 101 b) 010 or 100 or 110 or 101 c) 000 or 010 or 110 or 100 d) 100 or 111 or 101 or 001
HCL,
1 7227A perceptron is: a) a single layer feed-forward neural network with pre-processing b) an auto-associative neural network c) a double layer auto-associative neural network d) a neural network that contains feedback
1 10037An auto-associative network is: a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing
1 17180A 4-input neuron has weights 1, 2, 3 and 4. The transfer function is linear with the constant of proportionality being equal to 2. The inputs are 4, 10, 5 and 20 respectively. The output will be: a) 238 b) 76 c) 119 d) 123
1 10086Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works. a) All of the mentioned are true b) (ii) and (iii) are true c) (i), (ii) and (iii) are true d) None of the mentioned
1 5044Which of the following is true for neural networks? (i) The training time depends on the size of the network. (ii) Neural networks can be simulated on a conventional computer. (iii) Artificial neurons are identical in operation to biological ones. a) All of the mentioned b) (ii) is true c) (i) and (ii) are true d) None of the mentioned
1 14707What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ‘computational’ rates a) (i) and (ii) are true b) (i) and (iii) are true c) Only (i) d) All of the mentioned
1 11714Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a picture are connected or not a) (ii) and (iii) are true b) (ii) is true c) All of the mentioned d) None of the mentioned
1 6334
What are the different methods for Sequential Supervised Learning?
How and by what methods data visualizations can be effectively used?
A problem solving approach works well for a) 8-Puzzle problem b) 8-queen problem c) Finding a optimal path from a given source to a destination d) Mars Hover (Robot Navigation)
State the difference between the expected value and mean value?
What's the “kernel trick” and how is it useful?
What is pragmatics natural language processing terminology?
How to handle missing data in a dataset in Machine Learning?
How would you screen for outliers and what should you do if you find one?
What are the steps involved in analytics projects?
What do you mean by dropout?
What is market basket analysis? How would you do it in r and python?
what is bias?
Which os is best for deep learning?
How is true positive rate and recall related? Write the equation.
How to avoid overflow in the logistic function?