Converted mixBerMnistEM to python (#344)
Converted mixBerMnistEM to python (#344)

* Converted mixBerMnistEM to python

Closes #174

The code might take some time to load and this is because it is downloading the MNIST dataset from online and the delay in execution is solely due to this and not due to the inefficiency of the code.

The values and the images will differ because the data is randomly chosen from the total set of images.

I initially added +1 to all images in the training set and changed the Bernoulli function to adapt to this, but did not see any change in the execution, It was more convenient for me to use the binary image as is and use the implementation of Bernoulli distribution which is used for this mixture model.

In this implementation, I did not find the optimal k because the optimal k=20 has already been found through trial and error in the MATLAB code and no graph implementation is found in the book.

* Update mixBerMnistEM.py

I made the suggested changes.
I set the N to 2000 for an execution time of 5 mins. 
Please change the n value in main() to test different training sizes.

* Removed Progress bar to avoid installing new modules
probml/pyprobml,probml/pyprobml,probml/pyprobml,probml/pyprobml