Explain concepts of Pooling in Convolutional Neural Network?
Ans: A pooling layer is one of the building blocks of a Convolutional Neural Network. Its function is to gradually
What do you mean by filtering, stride and padding in Convolutional Neural Network?
Ans: FilterA filter is represented by a vector of weights which we convolve the input. Every network layer act like
What is Convolutional Neural Network? What are all the layers used in it?
Ans: A Convolutional Neural Network is a Deep Learning algorithm which can take image as an input, assign weights and
IIT Hyderabad researchers develop method to access the inner workings of AI
Previously researchers have developed Artificial intelligence and with that many inventions have been taken place in every field like Medical,
What might be the reasons of the Neural Network model is unable to decrease loss during training period?
Ans: Large Learning rate will cause the optimization to diverge, small learning rate will prevent you from making real improvement,
What is Learning rate and how can it effect accuracy and performance in Neural Networks?
Ans: A neural network learns or approaches a function to best map inputs to outputs from examples in the training
How can you avoid local minima to achieve the minimized loss function?
Ans: We can try to prevent our loss function from getting stuck in a local minima by providing a momentum
What are Local Minima and Global Minima in Gradient Descent?
Ans: Local minima:The point in a curve which is minimum when compared to its preceding and succeeding points is called
What is the difference between Adagrad, Adadelta and Adam?
Ans: Adagrad:Adagrad scales alpha for each parameter according to the history of gradients (previous steps) for that parameter which is
Explain about Adam Optimization Function?
Ans: Adam can be looked at as a combination of RMSprop and Stochastic Gradient Descent with momentum. It uses the