Jurat jshayiding

## ngrams.py
"""Print most frequent N-grams in given file.

Usage: python ngrams.py filename

Problem description: Build a tool which receives a corpus of text,
analyses it and reports the top 10 most frequent bigrams, trigrams,
four-grams (i.e. most frequently occurring two, three and four word
consecutive combinations).

NOTES

## imdb_cnn_kim_small_embedding.py
'''This scripts implements Kim's paper "Convolutional Neural Networks for Sentence Classification"
with a very small embedding size (20) than the commonly used values (100 - 300) as it gives better
result with much less parameters.

Run on GPU: THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python imdb_cnn.py

Get to 0.853 test accuracy after 5 epochs. 13s/epoch on Nvidia GTX980 GPU.
'''

from __future__ import print_function
	"""Print most frequent N-grams in given file.

	Usage: python ngrams.py filename

	Problem description: Build a tool which receives a corpus of text,
	analyses it and reports the top 10 most frequent bigrams, trigrams,
	four-grams (i.e. most frequently occurring two, three and four word
	consecutive combinations).

	NOTES
	'''This scripts implements Kim's paper "Convolutional Neural Networks for Sentence Classification"
	with a very small embedding size (20) than the commonly used values (100 - 300) as it gives better
	result with much less parameters.

	Run on GPU: THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python imdb_cnn.py

	Get to 0.853 test accuracy after 5 epochs. 13s/epoch on Nvidia GTX980 GPU.
	'''

	from __future__ import print_function