Visualization of zero-one loss in W3D1 tutorial 2 is returning error as aliases of built-in types is deprecated

[ritog]

As per Numpy's release notes, using the aliases of builtin types like np.int is deprecated.

Yet, it is used in one of the tutorial notebooks. I noticed it.

This is the error message that you see, if you try to visualize Zero-one loss in the interactive demo 3, under section 3.1:

AttributeError: module 'numpy' has no attribute 'float'.

Full error message

---------------------------------------------------------------------------

AttributeError                            Traceback (most recent call last)

[/usr/local/lib/python3.11/dist-packages/ipywidgets/widgets/interaction.py](https://localhost:8080/#) in observer(change)
     78         with out:
     79             clear_output(wait=True)
---> 80             f(**kwargs)
     81             show_inline_matplotlib_plots()
     82     for k,w in controls.items():

3 frames

[/usr/local/lib/python3.11/dist-packages/numpy/__init__.py](https://localhost:8080/#) in __getattr__(attr)
    392 
    393         if attr in __former_attrs__:
--> 394             raise AttributeError(__former_attrs__[attr])
    395 
    396         if attr in __expired_attributes__:

AttributeError: module 'numpy' has no attribute 'float'.
`np.float` was a deprecated alias for the builtin `float`. To avoid this error in existing code, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

Here's a screenshot, when Zero-One Loss is selected:

However, it works fine for other losses. One example:

[ritog]

PR #1169 solves this.