C1 W3 Unq C6 Index Error

Course Q&A Machine Learning Specialization Supervised ML: Regression and Classification
1

In C1 W3 Logistic regression UNQ C6, I am getting an error as:
“IndexError: invalid index to scalar variable.”

Is there something wrong with my code? I am not able to understand why this is happening.
I am attaching the code snippet here. Please help.

UNQ_C6

def compute_gradient_reg(X, y, w, b, lambda_ = 1):
“”"
Computes the gradient for linear regression

Args:
  X : (ndarray Shape (m,n))   variable such as house size 
  y : (ndarray Shape (m,))    actual value 
  w : (ndarray Shape (n,))    values of parameters of the model      
  b : (scalar)                value of parameter of the model  
  lambda_ : (scalar,float)    regularization constant
Returns
  dj_db: (scalar)             The gradient of the cost w.r.t. the parameter b. 
  dj_dw: (ndarray Shape (n,)) The gradient of the cost w.r.t. the parameters w. 

"""
m, n = X.shape

dj_db, dj_dw = compute_gradient(X, y, w, b)

### START CODE HERE ###

{moderator edit: code removed

### END CODE HERE ###         
    
return dj_db, dj_dw

X_mapped = map_feature(X_train[:, 0], X_train[:, 1])
np.random.seed(1)
initial_w = np.random.rand(X_mapped.shape[1]) - 0.5
initial_b = 0.5

lambda_ = 0.5
dj_db, dj_dw = compute_gradient_reg(X_mapped, y_train, initial_w, initial_b, lambda_)

print(f"dj_db: {dj_db}“, )
print(f"First few elements of regularized dj_dw:\n {dj_dw[:4].tolist()}”, )

UNIT TESTS

compute_gradient_reg_test(compute_gradient_reg)

C1 W3 Unq C6
C1 W3 Unq C61271×672 80.6 KB

2

Hi @vyomrastogi ,

The problem is in the line of code for adding the regularization term to the corresponding element of dj_dw. Indexing to the element is by j, so it should be dj_dw[j] and not dj_dw which is a vector.

3

hi @Kic ,
Thankyou very much for the prompt response.
That helped me in getting the correct solution.

4

I’ve deleted the code from your post, since we’re not supposed to share our code on the forum.