Ramp - Rapid Machine Learning prototyping in Python

I'm doing a machine-learning project for my company (Sauce Labs) and decided to give Ramp a try. Despite some effort put into understanding the API and digging into code to ensure I was passing in all the right kinds of parameters when I hit random errors, I think it was worth it. I was able to test and compare 20 different machine learning algorithms and even more feature sets really easily. I'd definitely recommend checking it out!

I don't know if it's this package or just Python in general, but I'm having a really hard time getting things up and running with the Kaggle insults example. To get going I ran

  pip install numpy
  pip install pandas
  pip install scikit-learn
  sudo apt-get install libyaml-dev
  pip install nltk
  pip install gensim
  pip install numexpr
  pip install Cython
  sudo apt-get install libhdf5-serial-dev
  pip install h5py
  pip install tables
  pip install ramp

But I'm still running into some numpy issue with the cross-validation loop (`for config in factory:`).