I have a problem with course 1 week 3 practice lab, exercise 2. My output does not match the expected output. Can anyone help, please?

Thanks!

I have a problem with course 1 week 3 practice lab, exercise 2. My output does not match the expected output. Can anyone help, please?

Thanks!

Hello @Ayse_Nehir_Cevik Welcome to the community!

In your problem, Firstly you should have to complete the code of compute_cost function perfectly. Like summation of cost for all training example and divide by training sample (m).

Here use the equations to complete the compute_cost function:

𝑙𝑜𝑠𝑠(𝑓𝐰,𝑏(𝐱(𝑖)),𝑦(𝑖)) = (−𝑦(𝑖)log(𝑓𝐰,𝑏(𝐱(𝑖)))−(1−𝑦(𝑖))log(1−𝑓𝐰,𝑏(𝐱(𝑖)))

𝑓𝐰,𝑏(𝐱(𝑖)) = 𝑔(𝐰⋅𝐱(𝐢)+𝑏), where g is the sigmoid function

Pseudocode:

Initialize loss equal to zero

for ith training example to total training example:

𝑓𝐰,𝑏(𝐱(𝑖)) = 𝑔(𝐰⋅𝐱(𝐢)+𝑏) [for multiply use numpy.dot() function]

𝑙𝑜𝑠𝑠(𝑓𝐰,𝑏(𝐱(𝑖)),𝑦(𝑖)) += (−𝑦(𝑖)log(𝑓𝐰,𝑏(𝐱(𝑖)))−(1−𝑦(𝑖))log(1−𝑓𝐰,𝑏(𝐱(𝑖)))

return cost/m