AI Deep Learning Interview Questions, Answers for Freshers and Experienced asked in various Company Job Interviews

AI Deep Learning Interview Questions

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What is the meaning of term weight initialization in neural networks?

Can relu function be used in output layer?

What are the deep learning frameworks or tools?

Explain data normalization.

What do you understand by tensors?

What are the issues faced while training in recurrent networks?

What is the use of the activation function?

What is model capacity?

Explain the different layers of cnn.

What do you understand by deep autoencoders?

How many types of activation function are available?

What is the use of deep learning in today's age, and how is it adding data scientists?

Explain the types of perceptron?

Describe the theory of autonomous form of deep learning in a few words.

What is the sigmoid function?

Un-Answered Questions { AI Deep Learning }

Explain the importance of lstm.

What is data normalization and why do we need it?

What is the difference between Batch Gradient Descent and Stochastic Gradient Descent?

Is 8gb ram enough?

Which laptop is good for deep learning?

What is deep learning and how does it relate to ai?

What is a gpu used for?

What is Deep Learning?

What are the supervised learning algorithms in deep learning?

What do you mean by deep learning?

Why is zero initialization not a good weight initialization process?

Is 16gb of ram a lot?

What are cuda cores good for?

What is deep learning, and how does it contrast with other machine learning algorithms?

What do you mean by dropout?

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