Sample Output:

_{Here you can see the question as a comment and my code but I got an error with (len)}

_{Any help please?}

def classify_examples (weights, test_examples): result = [] for i in range(len(test_examples)): res = weights (0) for j in rangel len(test_examples[0])): res+=weights [j+1]*test_examples[i][j] if res<: result.append else: bi pts this function classifies examples using the perceptron algorithm. to do that it receives one single dimensional numpy array weights and then returns a with classification results for each example is positive if negative parameters: weights: bias in position test_examples: feature-values of test examples. note: width columns test_examples should be length assume features vectors follow same order: e.g. we wi w2 w3... x1 x2 x3... returns: either or return result w="np.array([-5," x="np.array(" hw.classify_examples out now pass them as an good luck :>