Neural Networks and Deep Learning Quiz

Which is true for Neural Networks?

• It has set of nodes and connections

• Each node computes it’s weighted input

• Node could be in excited state or non-excited state

• all of the mentioned

What is an activation value?

• weighted sum of inputs

• threshold value

• main input to neuron

• none of the mentioned

The process of adjusting the weight is known as?

• activation

• synchronization

• learning

• none of the mentioned

Supervised learning differs from unsupervised learning, in that supervised learning requires

• at least one input attribute

• input attributes to be categorical

• at least one output attribute

• output attributes to be categorical

Which of the following is not an example of an unsupervised neutral network?

• Self-organizing feature map

• Hebb network

• Both 1 and 2

• Back propagation network

How many layers Deep learning algorithms are constructed?

• 2

• 3

• 4

• 5

Which of the following is/are Limitations of deep learning?

• Data labeling

• Obtain huge training datasets

• Both A and B

• None of the above

The CPN provides practical approach for implementing?

• Pattern approximation

• Pattern mapping

• Pattern classification

• Pattern clustering

In feedforward network, the associations corresponding to input – output patterns are stored in?

• activation state

• input layer

• hidden layer

• none of the mentioned

What type of learning is involved in ART?

• supervised

• Unsupervised

• supervised and unsupervised

• None of the mentioned