https://d2l.ai/chapter_appendix-mathematics-for-deep-learning/geometry-linear-algebraic-ops.html

Please review the section 17.1.8. Determinant.

The example matrix A is different from matrix A presented in 17.1.4. Geometry of Linear Transformations.

I think columns and rows need to exchanged in 17.1.8.

Hi @mathnow, thanks for your feedback! We have corrected it at https://github.com/d2l-ai/d2l-en/pull/722.

```
%matplotlib inline
import d2l
from IPython import display
from mxnet import gluon, np, npx
npx.set_np()
def angle(v, w):
return np.arccos(v.dot(w) / (np.linalg.norm(v) * np.linalg.norm(w)))
orthogonal_angle = angle(np.array([0, 1]), np.array([1, 0]))
orthogonal_angle.asscalar()
```

raise bug:

Hi @chibinjiang, both of the following methods can change it to scalar:

float(orthogonal_angle)

or

orthogonal_angle.item()

@gold_piggy Appreciate

But why does `.asscalar()`

not work???

As you see, the `orthogonal_angle `

has the attribute of `asscalar()`

method.

There is not attribute of `asscalar`

in `np`

interface. Here are all the supported functions. http://numpy.mxnet.io/api/deepnumpy/index.html

Under Fig. 18.1.3, the vector 𝐮−𝐯 is the direction that takes us from the point 𝐯 to the point 𝐮, right?