Deep Learning - Deep Neural Network for Beginners Using Python - Linear to Non-Linear Boundaries

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Information Technology (IT), Architecture, Physics, Science
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University
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Hard
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5 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a major drawback of using linear boundaries for classification?
They are too complex to implement.
They are only applicable to small datasets.
They can misclassify data that is not linearly separable.
They require a lot of computational power.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why might a nonlinear boundary be preferred over a linear one?
They can handle data that is not linearly separable.
Nonlinear boundaries are easier to visualize.
Nonlinear boundaries are faster to compute.
They require less data to train.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How can multiple linear boundaries be used to create a nonlinear boundary?
By combining them using logical operations.
By using only the vertical boundaries.
By ignoring the less accurate ones.
By averaging their results.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which logical gate can be used to combine linear boundaries?
NOT gate
NAND gate
NOR gate
AND gate
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the goal of combining linear boundaries?
To simplify the data analysis process.
To reduce the number of data points.
To create a more complex model.
To form a nonlinear boundary for better classification.
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