What is the difference between Momentum and Nesterov Momentum?
Ans: Momentum method is a technique that can speed up gradient descent by taking accounts of previous gradients in the
Explain Momentum in Gradient Descent?
Ans: Generally, in Deep Neural Networks we train the noisy data. To reduce the effect of noise when the data
What do you mean by RMS Prop?
Ans: RMS Prop is an optimization technique which is not published yet used for Neural Networks. To know about RMS
Explain Gradient Descent is going to help to minimize loss functions?
Ans: Gradient descent is an optimization algorithm used to minimize loss function by iteratively moving in the direction of steepest descent
Explain brief about Mini Batch Gradient Descent?
Ans: Mini-batch gradient descent is an extension of the gradient descent algorithm. Mini batch gradient descent splits the training dataset
Explain different optimization algorithms that we generally use in Neural Network?
Ans: Optimizers are algorithms or methods used to change the attributes of your neural network such as weights and learning
Explain difference between sparse categorical cross entropy and categorical entropy?
Ans: For both sparse categorical cross entropy and categorical cross entropy have same loss functions but only difference is the
Explain different Loss functions that we generally use for Neural Networks?
Ans: There are no specific loss functions used for Neural Networks. In general, we use Classification Loss Functions in Neural
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What are the different Gradient Descent implementations/ methods?
Ans. There are different implementations of Gradient Descent which are used for minimizing cost functions.Batch Gradient Descent: It processes all the