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..

The diagram in documentation suggest yes, but num_fc_layers and fc_layers are not listed as available parameters as they are for e.g., parallel cnn or stacked cnn.

It does not seem like it is supported based on a few experiments however I am using the RNN encoder inside a sequence combiner, so possibly this is causing problems.

for example, this does not seem to add any fc_layers:

co

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!

I think would be very nice to have somewhere to share thoughts and meet other people experimenting stent in their project.

@krasimir could you create it for us?

Note:
I just would like to add that I think your project is just awesome and underestimated. I am loving to use it in my project

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

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

Currently there are a few which contains functionality that is rarely used, or that doesn't quite fit into the current direction of the package. This includes:

• SharpLearning.Containers.Arithmetic: MatrixF64 is mostly used as a container, and more efficient matrix arithmetic can found in other libraries, like mathnet.numerics.
• SharpLearning.Containers.ObservationTargetSet: This can be r