What are Tensors?DNN framework Interview Questions for freshers/DNN framework Interview Questions and Answers for Freshers & Experienced

What are Tensors?

Tensors are nothing but a de facto for representing the data in deep learning. They are just multidimensional arrays, that allows you to represent data having higher dimensions. In general, Deep Learning you deal with high dimensional data sets where dimensions refer to different features present in the data set.

Posted Date:- 2022-02-15 12:07:46

Explain the importance of LSTM.

What is Exploding Gradient Descent?

What is Vanishing Gradient? And how is this harmful?

What are some issues faced while training an RNN?

What is an RNN?

Explain the different Layers of CNN.

What is a CNN?

What is Computational Graph?

List a few advantages of TensorFlow?

What are Tensors?

Name a few deep learning frameworks

In training a neural network, you notice that the loss does not decrease in the few starting epochs. What could be the reason?

What is Dropout?

What are the Hperparameteres? Name a few used in any Neural Network.

What’s the difference between a feed-forward and a backpropagation neural network?

Why is Weight Initialization important in Neural Networks?

Which is Better Deep Networks or Shallow ones? and Why?

What Is Data Normalization And Why Do We Need It?

What are the different parts of a multi-layer perceptron?

What is a Multi-Layer-Perceptron

What are the shortcomings of a single layer perceptron?

What are the steps for using a gradient descent algorithm?

What are the benefits of mini-batch gradient descent?

What is gradient descent?

What is the significance of a Cost/Loss function?

Explain Learning of a Perceptron.

What are the activation functions?

What is the role of weights and bias?

What is Perceptron? And How does it Work?

Do you think Deep Learning is Better than Machine Learning? If so, why?

Which deep learning algorithm is the best for face detection?

Explain Stochastic Gradient Descent. How is it different from Batch Gradient Descent ?

Explain Batch Gradient Descent.

In a Convolutional Neural Network (CNN), how can you fix the constant validation accuracy?

Explain the difference between a shallow network and a deep network.

What is a tensor in deep learning?

Is it possible to train a neural network model by setting all biases to 0? Also, is it possible to train a neural network model by setting all of the weights to 0?

What are the advantages of transfer learning?

Explain transfer learning in the context of deep learning.

What do you mean by hyperparameters in the context of deep learning?

Explain Data Normalisation. What is the need for it?

Explain Forward and Back Propagation in the context of deep learning.

What do you understand about gradient clipping in the context of deep learning?

What do you mean by end-to-end learning?

What are the different types of deep neural networks?

Explain what a deep neural network is.

What are the disadvantages of neural networks?

What are the advantages of neural networks?

Explain learning rate in the context of neural network models. What happens if the learning rate is too high or too low?

What are the applications of deep learning?

Differentiate between AI, Machine Learning and Deep Learning.

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