APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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A neuron computes an activation function followed by a linear function (z = Wx + b)
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A neuron computes a linear function (z = Wx + b) followed by an activation function
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A neuron computes a function g that scales the input x linearly (Wx + b)
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A neuron computes the mean of all features before applying the output to an activation function
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Detailed explanation-1: -Neural computation is the information processing performed by networks of neurons. Neural computation is affiliated with the philosophical tradition known as Computational theory of mind, also referred to as computationalism, which advances the thesis that neural computation explains cognition.
Detailed explanation-2: -1) Linear Activation Functions A linear function is also known as a straight-line function where the activation is proportional to the input i.e. the weighted sum from neurons. It has a simple function with the equation: f(x) = ax + c. The problem with this activation is that it cannot be defined in a specific range.
Detailed explanation-3: -A neural network is a method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain. It is a type of machine learning process, called deep learning, that uses interconnected nodes or neurons in a layered structure that resembles the human brain.
Detailed explanation-4: -The basic computational unit of the brain is a neuron.