Deep Learning - Recurrent Neural Networks with TensorFlow - Proof That the Linear Model Works

Deep Learning - Recurrent Neural Networks with TensorFlow - Proof That the Linear Model Works

Assessment

Interactive Video

Mathematics

11th - 12th Grade

Hard

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The video tutorial explores how linear regression can predict a sine wave, a non-linear function, using an AR2 model without a bias term. It delves into the mathematical representation of sine waves and demonstrates how recurrence relations, similar to the Fibonacci sequence, can be used in the AR2 model. The tutorial also revisits trigonometric identities to aid in the derivation process, ultimately proving that a sine wave can be represented as a recurrence relation.

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5 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the significance of the AR2 model in predicting a sine wave?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain how the sine wave function is represented mathematically in the context of time series.

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the relationship between the Fibonacci equation and the AR2 model?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the manipulation of the sine Omega T equation as discussed in the text.

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

How do the constants W1 and W2 relate to the representation of the sine wave as a recurrence relation?

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