Artificial Intelligence For Engineering Quizzes Part 7

Q:1. Applications of Deep Learning are:

1.Self-driving cars

2.Fake news detection

3.Virtual Assistants

4.All the above

Solution- 4. All the above

Reason- Self-driving cars, Fake news detection and virtual assistants all are the applications of deep learning including healthcare, fraud detection etc..

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Q:2. The inputs for a single layer neural network are 1, 3, 2 and the weights of links connecting input neurons to the output neuron are 2, 2, and 3 then the output will be (Identity activation function is used in output neuron):

1.6

2.14

3.12

4.None of the above

Solution- 2. 14

Reason- by using this formula – Output = w1 * x1 + w2 * x2 + w3 * x3

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Q:3. Which of the following is not a type of Artificial Neural Network?

1.Perceptron

2.Radial Basis Functions

3.Random Forest

4.Autoencoder

Solution- 3. Random Forest

Reason- Both the Random Forest and Neural Networks are different techniques that learn differently but can be used in similar domains. Random Forest is a technique of Machine Learning while Neural Networks are exclusive to Deep Learning.

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Q:4. What is the limitation of deep learning?

1.Amount of data

2.Computational expensive

3.Data Labeling

4.All the above

Solution- 4. All the above

Reason- Amount of data, computational expenses and data labelling all three are the limitation of deep learning.

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Q:5. The number of nodes in the hidden layer is 8 and the output layer is 5. The maximum number of connections from the hidden layer to the output layer are:

1.40

2.Less than 40

3.More than 40

4.It is an arbitrary value

Solution- 1. 40

Reason- it is a fully connected direct graph, the number of connections are multiple of nodes in hidden layer and output layer.

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Q:6. Recurrent Neural Networks (RNN) are used for

1.Businesses Help securities traders to generate analytic reports

2.Detecting fraudulent credit-card transaction

3.Providing a caption for images

4.All of the above

Solution- 4. All of the above

Reason- All of the above options are true. This is because RNN is used to Help securities traders to generate analytic reports, Detecting fraudulent credit-card transaction and to provide a caption for images.

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Q:7. Types of RNN are:

1.LSTM

2.Boltzman machine

3.Hopfield network

4.a and b

Solution- 4. a and b

Reason- A Boltzmann machine (also called stochastic Hopfield network with hidden units or Sherrington–Kirkpatrick model with external field or stochastic Ising-Lenz-Little model) is a type of stochastic recurrent neural network. LSTM networks are a type of RNN that uses special units in addition to standard units.

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Q:8. What is perceptron?

1.a single layer feed-forward neural network with pre-processing

2.an auto-associative neural network

3.a double layer auto-associative neural network

4.a neural network that contains feedb

Solution- 1. a single layer feed-forward neural network with pre-processing

Reason- It is the simplest type of feedforward neural network , a feedforward neural network with no hidden units. Thus, a perceptron has only an input layer and an output layer.

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Q:9. Which of the following architecture has feedback connections?

1.Recurrent Neural network

2.Convolutional Neural Network

3.Restricted Boltzmann Machine

4.None of these

Solution- 2.Convolutional Neural Network

Reason- CNN is a feed forward neural network that is generally used for Image recognition and object classification.

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Q:10. Bidirectional RNN:

1.Trained to predict both the positive and negative directions of time simultaneously.

2.Applications are speech recognition, handwritten recognition etc.

3.After forward and backward passes are done, the weights are updated

4.All the above

Solution- 4. All the above

Reason- All the above options are true.

Disclaimer-

This article only attempts to discover some questions that can be generated in Artificial Intelligence For Engineering with the answer to all these questions. There can be some errors to these answers. If you find any error then please do write to us.