function [grad_W, grad_b] = Compute_Gradients(X, Y, P, W, lambda)

 

d = size(X, 1);

N = size(X, 2);

 

n_b = 1;

ones_n_b = double(zeros(n_b, 1) + 1);

random_data_indices = randsample(N, n_b, true);

 

X_Batch = X(:, random_data_indices)

Y_Batch = Y(:, random_data_indices)

P_Batch = P(:, random_data_indices)

 

G_Batch = -(Y_Batch - P_Batch)

 

grad_W = (1 / n_b) * G_Batch * X_Batch' + 2 * lambda * W;

grad_b = (1 / n_b) * G_Batch * ones_n_b;

 

 

 

 

 

 

function P = Evaluate_Classifier(X, W, b)

 

N = size(X, 2);

K = size(W, 1);

P = zeros(K, N);

 

for column = 1:N

    s = W * X(:,column) + b;

    p = exp(s);

    p = p / sum(p);

    P(:,column) = p;