Tensorflow 2

Q1. 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
I don't know
Yes
No

Q2. Can a neural network model the characteristic (y=1/x) in TensorFlow?

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

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

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

Q4. Identify the lifeless unit in a neural community?

The unit which produces the most important sum-squared mistakes
None of the above
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

Q5. In a neural network, which of the subsequent strategies is used to deal with overfitting in TensorFlow?

Regularization
All of the above
Dropout
Batch normalization

Q6. 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
A neuron has a single input, however, more than one outputs
All of the above statements are valid

Q7. Which of the following functions shouldn't be used at the output layer to classify an image?

None of these
tanh
sigmoid
ReLU

Q8. Wherein neural internet architecture, does weight sharing occur in TensorFlow?

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

Q9. What if we use a gaining knowledge of fee that’s too huge?

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

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

None of the above
Stacking
Bagging
Boosting

Your Score

- of - questions are answered correctly

Deep Learning with TensorFlow 2

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