Herbert prhbrt

## Holistically-Nested Edge Detection Paper Example.ipynb

      
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              January 9, 2019 09:41
            
              
                Holistically-Nested Edge Detection Paper Example
              
          
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## GloVe txt to gensim word2vec model.py
import numpy
from gensim.models.keyedvectors import Vocab, KeyedVectors

# Covert the Twitter datasets found here to gensim word2vec format: https://github.com/3Top/word2vec-api

with open('glove.6B.300d.txt') as fin:
    word_vecs = {
        word: numpy.array(list(map(float, vec.split())))
        for line in fin
        for word, vec in [line.split(' ', 1)]

## Paalplekken.ipynb

      
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                / Paalplekken.ipynb
            
            
              Created
              August 4, 2017 09:38
            
          
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## Paalplekken.ipynb

      
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                / Paalplekken.ipynb
            
            
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              August 4, 2017 09:35
            
              
                Paalplekken of logerenbijdeboswachter, places in Holland where you're allowed to camp free(ish)ly
              
          
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## MNIST vanishing gradient.ipynb

      
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                / MNIST  vanishing gradient.ipynb
            
            
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              April 19, 2017 07:23
            
          
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## Backspace.ipynb

      
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                / Backspace.ipynb
            
            
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              February 23, 2017 13:38
            
          
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## Keras.ipynb

      
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                / Keras.ipynb
            
            
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              January 19, 2017 15:59
            
              
                V-Net in Keras and tensorflow
              
          
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## IMDB + TFIDF + LogReg.ipynb

      
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              March 25, 2019 05:38
            
              
                Notebook of TFIDF Logistic regression on IMDB sentiment dataset (provided by keras)
              
          
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	import numpy
	from gensim.models.keyedvectors import Vocab, KeyedVectors

	# Covert the Twitter datasets found here to gensim word2vec format: https://github.com/3Top/word2vec-api

	with open('glove.6B.300d.txt') as fin:
	word_vecs = {
	word: numpy.array(list(map(float, vec.split())))
	for line in fin
	for word, vec in [line.split(' ', 1)]