regression

Hi I would like to propose a better implementation for 'test_indices':

We can remove the unneeded np.array casting:

Cleaner/New:
test_indices = list(set(range(len(texts))) - set(train_indices))

Old:
test_indices = np.array(list(set(range(len(texts))) - set(train_indices)))

Is your feature request related to a problem? Please describe.
In time series plotting module, lot of plots are customized at the end - template, fig size, etc. Since the same code is repeated in all these plots, maybe this could be modularized and reused.

with fig.batch_update():
    template = _resolve_dict_keys(
        dict_=fig_kwargs, key="template", defaults=fig_default

What is the desired addition or change?

provide a cmake c++17 switch

What is the motivation for this feature?

to not depend on the std_backport

If applicable, describe how this feature would be implemented.

change those lines from 11 to 17 conditional to a global define

https://github.com/mlpack/mlpack/blob/de94eee6881e33f1145d9d4a8b5380a5be8af36a/CMakeLists.txt#L

ray.init(n_cpus=16)
should be
ray.init(num_cpus=16) in the documentation page
https://microsoft.github.io/FLAML/docs/Use-Cases/Task-Oriented-AutoML#parallel-tuning

Hi @JavierAntoran @stratisMarkou,

First of all, thanks for making all of this code available - it's been great to look through!

Im currently spending some time trying to work through the Weight Uncertainty in Neural Networks in order to implement Bayes-by-Backprop. I was struggling to understand the difference between your implementation of `Bayes-by-Bac