C1_W4_Assignment

Course Q&A Math for Machine Learning Linear Algebra for Machine Learning and Data Sc...
1

Hello,

I am doing the C1_W4 programming assignment and I am stuck on exercise 3.

I have the following:

### START CODE HERE ###
P = np.array([    
    [0, .75, .30, .75, .10],
    [.10, 0, .30, .05, .30],
    [.30, .12, 0, .10, .55],
    [.55, .05, .30, 0, .05],
    [.05, .08, .10, .10, 0]
]) 
X0 = np.array([[0], [0], [0], [1], [0]])
# Multiply matrix P and X_0 (matrix multiplication).
X1 = np.matmul(P,X0)

### END CODE HERE ###
print(sum(P))

When I run the test:

# Test your solution.
w4_unittest.test_matrix(P, X0, X1)
Wrong vector X1. Check if matrix multiplication was performed correctly.
 6  Tests passed
 1  Tests failed

I am not sure what I am doing wrong with the matrix multiplication for X1?

Any insight as to my mistake is greatly appreciated.

2

Hi, I am also getting the same error. Not sure what’s wrong with the result. Does the test expect to have specific number in the matrix P?


### START CODE HERE ###
P = np.array([    
    [0,     0.25,   0.35,   0.15,   0.35],
    [0.15,  0,      0.35,   0.05,   0.15],
    [0.30,  0.20,   0,      0.20,   0.20],
    [0.20,  0.10,   0.20,   0,      0.30],
    [0.35,  0.45,   0.10,   0.60,   0   ]
]) 
X0 = np.array([[0], [0], [0], [1], [0]])
# Multiply matrix P and X_0 (matrix multiplication).
​
​
X1 = P @ X0
​
print(X1.shape)
print(X1)
### END CODE HERE ###
print(sum(P))

This is the result I got:


Wrong vector X1. Check if matrix multiplication was performed correctly.
 6  Tests passed
 1  Tests failed
3

There is a hard coded P matrix in the unittest script which is compared with the P matrix we used in the code. Don’t know why they have this comparison.


def test_matrix(target_P, target_X0, target_X1):
    successful_cases = 0
    failed_cases = []

    test_cases = [
        {
            "name": "default_check",
            "expected": {
                "P": np.array(
                    [
                        [0, 0.75, 0.35, 0.25, 0.85],
                        [0.15, 0, 0.35, 0.25, 0.05],
                        [0.15, 0.15, 0, 0.25, 0.05],
                        [0.15, 0.05, 0.05, 0, 0.05],
                        [0.55, 0.05, 0.25, 0.25, 0],
                    ]
                ),
                "X0": np.array([[0], [0], [0], [1], [0]]),
            },
        },
    ]
4

Thanks for finding that out!

5

I am following this thread, I have the same error. Then I assume this is something that might need to be fixed on deeplearning.ai side

6

Thanks for finding that out! There is no way any one could come up with that specific matrix given the problem statement.

image
image1006×306 16 KB

7

Very true, as the only logic defined is that the main diagonal should be 0 and the columns adds to 1.