Practice Deep Learning And Neural Networks (8) - Deep Learning and Neural Networks

Practice: Deep Learning and Neural Networks

Lesson 8Deep Learning and Neural Networks

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8 questions

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6 sample questions

Question 1.
What are the three main layers in a neural network?
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Think about how the model receives input, processes it, and outputs a result.
Question 2.
Name one common activation function.
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It helps determine the output of neurons.
3Question 3.
What does the Sigmoid function do?
- Outputs values between -1 and 1
- Squashes input to (0, 1)
- Provides linear output
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Remember what happens to input values in the activation function.
4Question 4.
True or False: Dropout randomly turns off neurons during training to prevent overfitting.
- True
- False
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Think about how this method impacts learning.
Question 5.
How would you implement dropout in a neural network, and what impact would it have on model performance?
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Consider how random removal helps combat overfitting.
Question 6.
Consider a scenario where you notice the vanishing gradient problem in your deep learning model. What strategies might you employ to alleviate this issue?
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Think about how adjusting layers can affect gradient flow.

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