Tensorflow 2

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

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

Q2. In a neural network, which of the subsequent strategies is used to deal with overfitting in TensorFlow?

All of the above
Batch normalization
Dropout
Regularization

Q3. A numeric variable can shop numeric values with a maximum of eight digits.

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

Q4. What if we use a gaining knowledge of fee that’s too huge?

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

Q5. 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
Yes
No
I don't know

Q6. Which of the following functions shouldn't be used at the output layer to classify an image?

sigmoid
tanh
None of these
ReLU

Q7. Can a neural network model the characteristic (y=1/x) in TensorFlow?

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

Q8. Identify the lifeless unit in a neural community?

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

Q9. Which of the subsequent declaration(s) effectively represents an actual neuron in TensorFlow?

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

Q10. Which of the following techniques perform comparable operations as the dropout in a neural community in TensorFlow?

Bagging
Boosting
None of the above
Stacking

Your Score

- of - questions are answered correctly

Deep Learning with TensorFlow 2

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