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‘DL Training and Optimization’ Interview Questions

Describe briefly the training process of a Neural Network model

Explain the basic architecture and training process of a Neural Network model? Discuss briefly the key hyper-parameters

What are the key hyper-parameters of a neural network model?

What is an activation function? What are the different types of activation functions? Discuss their pros and cons

What is an activation function, and what are some of the most common choices for activation functions?

What are some guidelines for choosing activation functions?

What are some options for making Backpropagation more efficient?

What are some options to address overfitting in Neural Networks?

What is Dropout?

What is Rectified Linear Unit (ReLU) activation function? Discuss its advantages and disadvantages

Discuss Softmax activation function

What is Sigmoid (logistic) activation function?

Discuss TanH activation function

What is the “dead ReLU” problem and, why is it an issue in Neural Network training?

What do you mean by saturation in neural network training? Discuss the problems associated with saturation

What do you mean by vanishing gradient and why is that a problem?

What is the vanishing/exploding gradient problem?

What are some ways to address the vanishing/exploding gradient issue?

Why is Zero-centered output preferred for an activation function?

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