i'm a newbie in programming. I try to use this library. it's very useful for me.
I want to show centroid in K-means clustering. how to show it? thank u so much..

If split is not "full" (ie: I only want to use training or validation or test data to run a test, for example) and I don't have a .hdf5 file, data is loaded anyway, but without honoring the split request.

Reference: https://github.com/uber/ludwig/blob/master/ludwig/data/preprocessing.py#L804-L840

The notebook seems to use a pre-trained model from https://github.com/awslabs/amazon-sagemaker-examples/blob/master/introduction_to_applying_machine_learning/xgboost_customer_churn/xgboost_customer_churn.ipynb. The notebook should refer to the data schema from the above example when discussing generated traffic and suggested constraints.

Cell Deploy the model to Amazon SageMaker. THIS REQU

Not sure if that's how its supposed to look like but I see question marks in the terminal as below.

It doesn't look right. Can you advise, please?

Please someone right a full guide on how to use it or a newly updated biolierplate, i'm new to node js and can't figure out things since weeks now!

This looks nice, but doesn't work for multiple processes. In general we can't ensure we're even on the same terminal....

 93       /**
 94        * FIXME: This will work for a single address space, but it's broken
 95        * for multiple over SHM, need to fix. -jcb nov 2019
 96        */
 97       std::lock_guard< std::mutex > lg( print< T, delim >::print_lock );

After running pip install moviebox on a Mac with Python 2.7 I get the following error when trying to run it:

Traceback (most recent call last):
  File "/usr/local/bin/moviebox", line 7, in <module>
    from moviebox.cli import main
  File "/usr/local/lib/python2.7/site-packages/moviebox/cli.py", line 6, in <module>
    from .recommender import recommender
  File "/usr/local/lib/pyth

could you add ensemble of all ml algorithms you trained as an example? I want to learn how to do it from you, thanks!

Would be nice to improve the docs, make it clearer, simpler and easy to understand.

Switching from the matrix class to multidimensional arrays requires adding extension methods to provide to expose the same members that the current matrix class does.