Gradient descent learning: Consider the following set of data points: input X1 desired X2 label 1...

  

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Gradient descent learning: Consider the following set of data points: input X1 desired X2 label 1 1 1 1 0 1 0 1 0 -1 -1 0 -1 0 0 -1 1 0 As the above table shows, the data points are categorized (labeled) in two groups specified by the labels "1" and "0". a) Use the gradient descent learning algorithm to train a single neuron perceptron on the data points given in the table above. Repeat the gradient descent algorithm for only 3 iterations. Assume the learning rate is 0.1 with initial weight vector of (1 1 1). Gradient descent learning: Consider the following set of data points: input X1 desired X2 label 1 1 1 1 0 1 0 1 0 -1 -1 0 -1 0 0 -1 1 0 As the above table shows, the data points are categorized (labeled) in two groups specified by the labels "1" and "0". a) Use the gradient descent learning algorithm to train a single neuron perceptron on the data points given in the table above. Repeat the gradient descent algorithm for only 3 iterations. Assume the learning rate is 0.1 with initial weight vector of (1 1 1).