Tensorflow 2

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

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

Q2. 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?

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

Q3. Identify the lifeless unit in a neural community?

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

Q4. Which of the following functions shouldn't be used at the output layer to classify an image?

None of these
ReLU
sigmoid
tanh

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

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

Q6. Can a neural network model the characteristic (y=1/x) in TensorFlow?

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

Q7. Which of the subsequent declaration(s) effectively represents an actual neuron in TensorFlow?

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

Q8. Which of the following techniques perform comparable operations as the dropout in a neural community in TensorFlow?

None of the above
Boosting
Bagging
Stacking

Q9. In a neural network, which of the subsequent strategies is used to deal with overfitting in TensorFlow?

Batch normalization
Dropout
Regularization
All of the above

Q10. A numeric variable can shop numeric values with a maximum of eight digits.

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

Your Score

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Deep Learning with TensorFlow 2

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