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If you have engaged yourself in preparing for Deep Learning interview then this blog post will surely be the best aid for you in your preparation. This blog post consists of some of the most frequently asked interview questions in Deep Learning. Building knowledge of these questions will surely help you during the time of your interview
- What Do You Know About Deep Learning?
Deep Learning can be interpreted as a subset of Machine Learning in Artificial Intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Deep Learning is otherwise known as deep neural learning or deep neural network
- Why Are Deep Networks Better Than Shallow Ones?
Shallow and deep networks are well capable to approximate any function. However, Deep Networks are having a higher level of accuracy & efficiency in terms of computation and number of parameters. Deep representations can be created at every layer by using Deeper networks. So it becomes possible for the network to learn a new, more abstract representation of the input.
- What Is A Backpropagation?
Backpropagation is a training algorithm which is designed to be used for a multilayer neural network. It also enables the error information from the end of the network to all the weights inside the network and thus allows for efficient computation of the gradient.
- Weight Initialization In Neural Networks?
Weight initialization is a very important step. With Bad weight it becomes almost impossible for the network to learn. Good initialization can lead to quicker convergence and better overall error. Biases can be generally initialized to zero. So weights should be set close to zero without being too small.
- What Is A Model Capacity?
Model Capacity is the ability to approximate any given function. Based on the levels of the model capacity, we can determine the amount of information that can be stored in the network.
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