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Deep Learning interview questions Part -1
1 โ What is data normalization? What’s the need for it? Data normalization is a process of transforming data from...
Read More โWhat is Tanh activation function?
The Tanh Activation function is a scaled and shifted version of the hyperbolic tangent function, a mathematical function frequently encountered...
Read More โWhat is PReLU and ELU activation function?
PReLU(Parametric ReLU) – PReLU is vital to the success of deep learning. It solves the problem with activation functions like...
Read More โDifference between Leaky ReLU and ReLU activation function?
What is an Activation Function? An activation function is a critical component in neural networks. It determines a neuron’s output...
Read More โWhat is ReLU and Sigmoid activation function?
The activation function is a nonlinear function that takes in the weighted sum and produces the output. They are used...
Read More โWhat is Vanishing and exploding gradient descent?
Vanishing and exploding gradient descent is a type of optimization algorithm used in deep learning. Vanishing Gradient Vanishing Gradient occurs...
Read More โWhat is forward and backward propagation in Deep Learning?
Forward propagation is a process in which the network’s weights are updated according to the input, output and gradient of...
Read More โWhat is multilayer perceptron?
A multi-layer perceptron is a type of artificial neural network. It has one or more hidden layers between the input...
Read More โDifference between machine learning and machine reasoning?
Machine Learning is a subset of artificial intelligence, which is a type of statistical learning. It provides computer programs with...
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Perceptron vs Neuron: What’s the Real Difference?
The difference between a perceptron and a neuron is something that people get mixed up about all the time. This...
Read More โWhat is perceptron?
The perceptron is a type of artificial neural network (ANN) that is designed to recognize patterns in data. It can...
Read More โWhat is L1 and L2 regularization in Deep Learning?
In deep learning, L1 and L2 regularization are regularization techniques used to penalize the model’s weights during the training process....
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