Task2.py with topic models using LSI and LDA added. Models are stored in a models folder
Task2 is updated with modules for generting topic models. Added HDP-LDA model. Need more analysis of topics generated
Task1.py modified
     explore_corpus is chnaged to create_counter to return counter object and no more prints the results. Also the new method takes punctuation symbols and stopwords as arguments. This allows userdefined punctuations and stopwords to be used for tokenization.
     run method is added that produces output for the most popular, least popular and the number of guitar types
     guitar_types_count method is changed to guitar_types to return unique types of guitar insted of length of the types
Task1.py has minor updates; problem in run function, counter varaible is local to create counter now, popular items methods takes counter as argument; Test folder added.
Task2 updated with document clustering method using topics
Task2.py modified to run LSI model, LDA model, and HDP with LDA model for topic modelling. Further the modules running these models runs kmeans algorithm for document clustering with reduced dimension given by the number of topics.

test_task.py added. Does not perform assertion features. But runs differetn model and generates output. Output stored in output folder within ml directory.
Several files added
Task3 modified