- Update to Version 0.12.0
  + Highlights
    * MarkovNetwork models have been added in and include both inference and structure learning.
    * Support for Python 2 has been depricated.
    * Markov network, data generator, and callback tutorials have been added in
    * A robust `from_json` method has been added in to __init__.py that can deserialize JSONs from any pomegranate model.
  + MarkovNetwork
    * MarkovNetwork models have been added in as a new probabilistic model.
    * Loopy belief propagation inference has been added in using the FactorGraph backend
    * Structure learning has been added in using Chow-Liu trees
  + BayesianNetwork
    * Chow-Liu tree building has been sped up slightly, courtesy of @alexhenrie
    * Chow-Liu tree building was further sped up by almost an order of magnitude
    * Constraint Graphs no longer fail when passing in graphs with self loops, courtesy of @alexhenrie
  + BayesClassifier
    * Updated the `from_samples` method to accept BayesianNetwork as an emission. This will build one Bayesian network for each class and use them as the emissions.
  + Distributions
    * Added a warning to DiscreteDistribution when the user passes in an empty dictionary.
    * Fixed the sampling procedure for JointProbabilityTables. 
    * GammaDistributions should have their shape issue resolved
    * The documentation for BetaDistributions has been updated to specify that it is a Beta-Bernoulli distribution. 
  + io
    * New file added, io.py, that contains data generators that can be operated on
    * Added DataGenerator, DataFrameGenerator, and a BaseGenerator class to inherit from 
  + HiddenMarkovModel
    * Added RandomState parameter to `from_samples` to account for randomness when building discrete models.
  + Misc
    * Unneccessary calls to memset have been removed, courtesy of @alexhenrie
    * Checking for missing values has been slightly refactored to be cleaner, courtesy of @mareksmid-lucid
    * Include the LICENSE file in MANIFEST.in and simplify a bit, courtesy of @toddrme2178
    * Added in a robust from_json method that can be used to deseralize a JSON for any pomegranate model.
  + docs
    * Added io.rst to briefly describe data generators
    * Added MarkovNetwork.rst to describe Markov networks
    * Added links to tutorials that did not have tutorials linked to them.
  + Tutorials
    * Added in a tutorial notebook for Markov networks
    * Added in a tutorial notebook for data generators
    * Added in a tutorial notebook for callbacks
  + CI
    * Removed unit tests for Py2.7 from AppVeyor and Travis
    * Added unit tests for Py3.8 to AppVeyor and Travis 
- Dropped python2 support    

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