COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Deep learning enables computers to learn from experience & understand the world in terms of a hierarchy of concepts
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Backpropagation helps to calculate the gradient of a loss function with respects to all the weights in the network
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Deep Learning is Symbolic AI
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Deep Learning involves training neural networks with many layers of units
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Detailed explanation-1: -Supervised Learning: A Basic Hybrid AI First of all, every deep neural net trained by supervised learning combines deep learning and symbolic manipulation, at least in a rudimentary sense. Because symbolic reasoning encodes knowledge in symbols and strings of characters.
Detailed explanation-2: -Symbolic AI is an approach that trains Artificial Intelligence (AI) the same way human brain learns. It learns to understand the world by forming internal symbolic representations of its “world”. Symbols play a vital role in the human thought and reasoning process.
Detailed explanation-3: -This is a general approach to convert a neural network into an analytic equation. The technique works as follows: Encourage sparse latent representations. Apply symbolic regression to approximate the transformations between in/latent/out layers. Compose the symbolic expressions.
Detailed explanation-4: -Machine learning and deep learning are both types of AI. In short, machine learning is AI that can automatically adapt with minimal human interference. Deep learning is a subset of machine learning that uses artificial neural networks to mimic the learning process of the human brain.