Is your feature request related to a problem? Please describe.
Other related issues: #408 #251
I trained a Chinese model for spaCy, linked it to [spacy's package folder]/data/zh (using spacy link) and want to use that for ludwig. However, when I tried to set the config for ludwig, I received an error, which tell me that there is no way to load the Chinese model.

ValueError: Key ch

Lately running into too many Sagemaker issues. Is there any unambiguous documentation on Sagemakers Instances? I could glean the following from different sources:

1. Sagemaker Instances, Sagemaker being a managed service, have nothing to do with EC2 instances.
2. Unlike EC2 console, Sagemaker console has no option to view limits or increase limits. One has to go directly to the support page a

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 read the article, the git documentation...but I don't know how to implement the state machine (stent( in my project. Any basic project example (more explanatory than the TODO example?)
_

I know you guys are focused on bringing more features to the lib, but it would be good to provide a bit better documentation and examples (I sent another post about this), so the ones willing to use the current version can fully understand what they can do with it..

E.g.

• I am not sure how to use signals, I can see raft::fileread uses raft::eof, but not sure what is done with it.
• I don't

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.

In Python XGBoost one can provide weights for each row of the data, see http://xgboost.readthedocs.io/en/latest/python/python_api.html#xgboost.XGBClassifier.fit. I tried to look for a way to specify such weights in SharpLearning, but could not find it. Is this possible?