Related Questions

Which 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.
Which 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.
You are the administrator of a Windows 2000 Server computer. The server contains one network adapter and is a file and print server for critical company resources. You install a second network adpater in the server and connect it to the same network subnet as the first adapter. You want to ensure that the first adapter is used for all network traffic and the second adapter is used only if the first adapter fails or is disconnected from the network. You also want to ensure that the server always has network connectivity even if one network adapter fails. What should you do?
A too-large weight initialized on the neural network can lead to vanishing gradient whereas a too-small weight initialized on the neural network can lead to exploding gradient.
Assume that you are given a data set and a neural network model trained on the data set. You are asked to build a decision tree model with the sole purpose of understanding/interpreting the built neural network model. In such a scenario, which among the following measures would you concentrate most on optimising?
Given above is a description of a neural network. When does a neural network model become a deep learning model?
Your network uses TCP/IP as the only network protocol. Devices on the network are configured to use IP address from the private 10.0.0.0 range. All the client computers on the network runs Windows 2000 Professional. The network includes Windows 2000 Server computers and UNIX servers. User's print jobs are sent to shared printers on a Windows 2000 Server computer named PrintServ that directs the print jobs to print devices attached directly to the network. You have a high-capacity print device that is attached to one of the UNIX servers. The UNIX computer uses the LPR printing protocol, and it's IP address is 10.1.1.99. The name of the printer queue is GIANT. You want users to be able to connect to this printer from their computers. What should you do?
Which 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.
Which 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.
Imagine, you are solving a classification problems with highly imbalanced class. The majority class is observed 99% of times in the training data. Your model has 99% accuracy after taking the predictions on test data. Which of the following is true in such a case?
1. Accuracy metric is not a good idea for imbalanced class problems.
2.Accuracy metric is a good idea for imbalanced class problems.
3.Precision and recall metrics are good for imbalanced class problems.
4.Precision and recall metrics aren't good for imbalanced class problems.