Hi all,

I am very new to this course and I am getting stuck at the Course 1/ WK2 asssignment: “Logistic regression with a Neural network mindset”.

I think i have written the code correct but its giving me an error.

My piece of code:**

{**CODES REMOVED BY MODERATOR, REFRAIN POSTING GRADER CODES FROM ASSIGNMENT IN FUTURE**}

YOUR CODE ENDS HERE

**Error i am getting:**

ValueError Traceback (most recent call last)

in

1 from public_tests import *

2

----> 3 model_test(model)

~/work/release/W2A2/public_tests.py in model_test(target)

123 y_test = np.array([[0, 1, 0]])

124

→ 125 d = target(X, Y, x_test, y_test, num_iterations=50, learning_rate=0.01)

126

127 assert type(d[‘costs’]) == list, f"Wrong type for d[‘costs’]. {type(d[‘costs’])} != list"

in model(X_train, Y_train, X_test, Y_test, num_iterations, learning_rate, print_cost)

36 # YOUR CODE STARTS HERE

37 w, b = initialize_with_zeros(X_train.shape[0])

—> 38 params, grads, costs = optimize(w, b, X, Y, num_iterations, learning_rate, print_cost)

39

40 Y_prediction_train = predict(w, b, X_train)

in optimize(w, b, X, Y, num_iterations, learning_rate, print_cost)

35 # grads, cost = …

36 # YOUR CODE STARTS HERE

—> 37 grads, cost = propagate(w, b, X, Y)

38

39 # YOUR CODE ENDS HERE

in propagate(w, b, X, Y)

31 # cost = …

32 # YOUR CODE STARTS HERE

—> 33 A = sigmoid(np.dot(w.T,X)+b)

34 cost = -(1/m)*np.sum(Y*np.log(A)+(1-Y)*np.log((1-A)))

35

<**array_function** internals> in dot(*args, **kwargs)

ValueError: shapes (1,4) and (2,3) not aligned: 4 (dim 1) != 2 (dim 0)

Thanks all for the help!