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The file Consts.py contains class Consts of the constants for the recommender system demo.

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The file Nets.py contains simple classes for the neural net and the autoencoder net.

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The file MIDS.py contains demo for base functions of the recommender system.

1. To prepare data for the recommender system demo user scripts from Rscripts and PrepareData folders. 

2. To train the recommender system demo set 
		train_mode = True
	in the module run if statement.
	and run
		python mids.py
		
3. To get nearest movies and convert npy ids files to the text format set 
		train_mode = False
	    	get_best_films_for_users_mode = False
	and run 
		python mids.py
	(may be your should set movie id(s) in function nearest_movies() at line 
		movie_ids = [1251] #,1974
	to see nearest movies for the specific movie ids)

4. To get best movies for rand users set 
	    	train_mode = False
	    	get_best_films_for_users_mode = True
        and set 
		 UserLines.main(14)
	id of folder to load model from.