New
* Added demo notebooks:
* [one](https://github.com/machine-intelligence-laboratory/TopicNet/blob/master/topicnet/demos/20NG-GenSim%20vs%20TopicNet.ipynb): some comparison of TopicNet with Gensim library
* [two](https://github.com/machine-intelligence-laboratory/TopicNet/blob/master/topicnet/demos/Making-Decorrelation-and-Topic-Selection-Friends.ipynb): example of analysis of the 20 Newsgroups dataset, more examples of how one can conduct topic modeling with the help of TopicNet and ARTM
* [three](https://github.com/machine-intelligence-laboratory/TopicNet/blob/master/topicnet/demos/20NG-PREPROCESSING.ipynb): more about 20 Newsgroups dataset analysis before actual topic modeling
Fixed
* Improved top tokens html display by TopTokensViewer
* Fixed TopicNet installation via pip: now all the necessary packages should be installed automatically.
So the command `pip install topicnet` should work just fine... for Linux :)
Future Plans
* Add new regularizers
* Add more abilities to control TopicModel's training process — with `model.fit()` function
* Make the library installable with `pip` also for Windows and Mac without BigARTM preinstalled