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# Perceptron

### Week – 2 Perceptron of Launching into Machine Learning

Perceptron
Linear regression
None of the above.
Neuron
Dendrites
Perceptron
All of the above
A perceptron is a type of sequential classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector.
A perceptron is a type of modular classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector.
A perceptron is a type of monitoring classifier.
A perceptron is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector.
Takes the inputs, multiplies them by their weights, and computes their sum.
Adds a bias factor, the number 1 multiplied by a weight.
Feeds the sum through the activation function.
All of the above
Input function x
Bias b
Activation function
All of the above
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### Generalization and ML Models

1. Which of the following is an algorithm for supervised learning of binary classifiers – given that a binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class.

1 point

2. Which model is the linear classifier, also used in Supervised learning?

1 point

3. Which of the following statements is correct?

1 point

4. What are the steps involved in the Perceptron Learning Process?

1 point

5. What are the elements of a perceptron?

1 point

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