Hi!, i’ve been trying to find my mistake in this code, someone please can help me, i think the problem is in the initialization of the parameters w and b. I just can’t figure it out how to do it.

# YOUR CODE STARTS HERE

```
w, b = initialize_with_zeros(dim)
```

parameters, grads, costs = optimize(w,b,X_train,Y_train,num_iterations = 2000, learning_rate = 0.05, print_cost = true)

```
w = params["w"]
b = params["b"]
Y_prediction_train =predict(w, b,X_train)
Y_prediction_test = predict(w, b,X_test)
```

and the errors are:

ValueError Traceback (most recent call last)

in

----> 1 model_test(model)

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

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

110

→ 111 d = target(X, Y, x_test, y_test, num_iterations=50, learning_rate=1e-4)

112

113 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)

37

38

—> 39 parameters, grads, costs = optimize(w,b,X_train,Y_train,num_iterations, learning_rate , print_cost)

40

41 w = params[“w”]

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 # YOUR CODE ENDS HERE

39

in propagate(w, b, X, Y)

31

32

—> 33 A = sigmoid(np.dot(w.T,X)+ b)

34 a1= (1-Y)

35 a2 = np.log(1-A)

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

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