David tmdavid

## word_embedding_vis.py
"""
Visualize word embeddings, using tsne.
First computes cosine distance of the 100 closests words, and then shows a clustering graph
of the first 11 closest words (the first one is always the word)
IT REQUIRES GLOVE MODEL.txt
line 31: glove_file = '../TBIR/glove.840B.300d.txt' MODIFY with the appropiate path

To Use it, you can just type: python word_embedding_vis.py <list of words space separated>
                              e.g: python word_embedding_vis.py cake word embedding music
"""
	"""
	Visualize word embeddings, using tsne.
	First computes cosine distance of the 100 closests words, and then shows a clustering graph
	of the first 11 closest words (the first one is always the word)
	IT REQUIRES GLOVE MODEL.txt
	line 31: glove_file = '../TBIR/glove.840B.300d.txt' MODIFY with the appropiate path

	To Use it, you can just type: python word_embedding_vis.py <list of words space separated>
	e.g: python word_embedding_vis.py cake word embedding music
	"""