kyttcar -3 years ago 407

Python Question

I am working through Andrew Ng new deep learning Coursera course, week2.

We are supposed to implement a logistic regression algorithm.

I am stuck at gradient code (

`dw`

The algorithm is as follows:

`import numpy as np`

def propagate(w, b, X, Y):

m = X.shape[1]

A = sigmoid(np.dot(w.T,X) + b ) # compute activation

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

dw =(1/m)*np.dot(X,(A-Y).T)

db = (1/m)*(np.sum(A-Y))

assert(dw.shape == w.shape)

assert(db.dtype == float)

cost = np.squeeze(cost)

assert(cost.shape == ())

grads = {"dw": dw,

"db": db}

return grads, cost

Any ideas why I keep on getting this syntax error?

`File "<ipython-input-1-d104f7763626>", line 32`

dw =(1/m)*np.dot(X,(A-Y).T)

^

SyntaxError: invalid syntax

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Answer Source

In the line `cost = ...`

, you are missing one parenthesis at the end, or just remove the one after `*`

:

```
# ...
cost = -(1/m)*np.sum(np.multiply(Y,np.log(A)) + np.multiply((1-Y),np.log(1-A)), axis=1)
# ...
```

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