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- import pandas as pd
- # TODO: Set weight1, weight2, and bias
- weight1 = 0.0,0.0,0.0,0.0
- weight2 = 0.0,0.0,0.0,0.0
- bias = 0.0,0.0,0.0,1.1
- # DON'T CHANGE ANYTHING BELOW
- # Inputs and outputs
- test_inputs = [(0, 0), (0, 1), (1, 0), (1, 1)]
- correct_outputs = [False, False, False, True]
- outputs = []
- # Generate and check output
- for test_input, correct_output in zip(test_inputs, correct_outputs):
- linear_combination = weight1 * test_input[0] + weight2 * test_input[1] + bias
- output = int(linear_combination >= 0)
- is_correct_string = 'Yes' if output == correct_output else 'No'
- outputs.append([test_input[0], test_input[1], linear_combination, output, is_correct_string])
- # Print output
- num_wrong = len([output[4] for output in outputs if output[4] == 'No'])
- output_frame = pd.DataFrame(outputs, columns=['Input 1', ' Input 2', ' Linear Combination', ' Activation Output', ' Is Correct'])
- if not num_wrong:
- print('Nice! You got it all correct.\n')
- else:
- print('You got {} wrong. Keep trying!\n'.format(num_wrong))
- print(output_frame.to_string(index=False))
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