f0nzie

9/7/2017 - 12:30 AM

Normalize rows of a matrix by dividing rows by the normal of the matrix

```
def normalizeRows(x):
"""
Implement a function that normalizes each row of the matrix x (to have unit length).
Argument:
x -- A numpy matrix of shape (n, m)
Returns:
x -- The normalized (by row) numpy matrix. You are allowed to modify x.
"""
# Compute x_norm as the norm 2 of x. Use np.linalg.norm(..., ord = 2, axis = ..., keepdims = True)
x_norm = np.linalg.norm(x, axis=1, keepdims=True)
print("x_norm.shape:", x_norm.shape, "\n")
# Divide x by its norm.
x = x / x_norm
return x
```