Tensorflow 2

Q1. Wherein neural internet architecture, does weight sharing occur in TensorFlow?

Recurrent Neural community
Convolutional neural community
b and c
Fully related Neural community

Q2. Identify the lifeless unit in a neural community?

A unit which doesn’t replace throughout training by means of any of its neighbour
A unit which does now not reply absolutely to any of the schooling styles
The unit which produces the most important sum-squared mistakes
None of the above

Q3. Which of the following techniques perform comparable operations as the dropout in a neural community in TensorFlow?

Stacking
Bagging
Boosting
None of the above

Q4. Can a neural network model the characteristic (y=1/x) in TensorFlow?

No
Can't be said
Yes
I don't know

Q5. What if we use a gaining knowledge of fee that’s too huge?

Can’t Say
Network will converge
Network will not converge
None of the above

Q6. Which of the subsequent declaration(s) effectively represents an actual neuron in TensorFlow?

All of the above statements are valid
A neuron has a single enter and a single output best
A neuron has multiple inputs but a single output only
A neuron has a single input, however, more than one outputs

Q7. A numeric variable can shop numeric values with a maximum of eight digits.

I don't know
No
Yes
Can't be said

Q8. Which of the following functions shouldn't be used at the output layer to classify an image?

sigmoid
None of these
ReLU
tanh

Q9. Y = ax^2 + bx + c (polynomial equation of degree 2)Can this equation be represented via a neural network of a single hidden layer with linear threshold?

Can't be said
No
I don't know
Yes

Q10. In a neural network, which of the subsequent strategies is used to deal with overfitting in TensorFlow?

Batch normalization
Regularization
All of the above
Dropout

Your Score

- of - questions are answered correctly

Deep Learning with TensorFlow 2

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