APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Neural network
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Random Forest
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k-Nearest neighbor
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None of the above
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Detailed explanation-1: -2) Which of the following is a representation learning algorithm? A) Neural networkB) Random ForestC) k-Nearest neighborD) None of the aboveSolution:(A)Neural network converts data in such a form that it would be better to solve the desired problem. This is called representation learning.
Detailed explanation-2: -Representation learning methods are considered in four main approaches: sub-space based, manifold based, shallow architectures, and deep architectures.
Detailed explanation-3: -Gradient descent is the recommended algorithm when we have massive neural networks, with many thousand parameters. The reason is that this method only stores the gradient vector (size n ), and it does not store the Hessian matrix (size n2 ).
Detailed explanation-4: -The three main types of learning in neural networks are supervised learning, unsupervised learning, and reinforcement learning.