Consider the dataset with 2 features fland f2 and two data points x1 and x2 and...

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Consider the dataset with 2 features fland f2 and two data points x1 and x2 and corresponding labels as y1 and y2 with real values. Consider below mentioned perceptron with weights w1 and w2 and y,and y2 are the predicted labels. a. Perform forward propagation and calculate loss using appropriate loss function b. Perform backward propagation using gradient descent to update the weights. Update weights for only 2 epochs. Xi1 Xiz W₁ W2 Σ Perceptron Vi ५. 2 f₁ 2 3 Dataset f₂ 4 5 y 2.0 4.0 Consider the dataset with 2 features fland f2 and two data points x1 and x2 and corresponding labels as y1 and y2 with real values. Consider below mentioned perceptron with weights w1 and w2 and y,and y2 are the predicted labels. a. Perform forward propagation and calculate loss using appropriate loss function b. Perform backward propagation using gradient descent to update the weights. Update weights for only 2 epochs. Xi1 Xiz W₁ W2 Σ Perceptron Vi ५. 2 f₁ 2 3 Dataset f₂ 4 5 y 2.0 4.0

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Heres how you can implement the forward and backward propagation steps using MATLAB for the given dataset and the perceptron model with two features f... View the full answer