Deep Learning - Deep Neural Network for Beginners Using Python - Implementing Basic Perceptron

Deep Learning - Deep Neural Network for Beginners Using Python - Implementing Basic Perceptron

Assessment

Interactive Video

Computers

9th - 10th Grade

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video tutorial explains the basic implementation of a perceptron using two features and weights. It starts by introducing variables and assigning values to them. A simple perceptron implementation is demonstrated, followed by a vectorized solution using Numpy for handling multiple features efficiently. The tutorial also covers testing the perceptron and handling errors related to mismatched features and weights.

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7 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What values are assigned to X1, X2, W1, W2, and B in the example?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain the simplest implementation of a perceptron as described in the text.

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What happens when the answer is greater than or equal to zero?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

How does the implementation handle multiple features and weights?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the role of the Numpy library in the perceptron implementation?

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6.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the function defined for the perceptron and its parameters.

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7.

OPEN ENDED QUESTION

3 mins • 1 pt

What error handling is suggested for mismatched numbers of features and weights?

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