Kelin Christi crikeli

## resizing_training_validation_and_test_data.ipynb

      
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                crikeli
                / resizing_training_validation_and_test_data.ipynb
            
            
              Created Apr 27, 2017
            
              
                Resizing and making sure data has indeed resized as we wanted...
              
          
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## resizing_image_function.ipynb

      
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                crikeli
                / resizing_image_function.ipynb
            
            
              Last active Apr 27, 2017
            
              
                resizing image function
              
          
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## plankton_visualtization_training_data.ipynb

      
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                / plankton_visualtization_training_data.ipynb
            
            
              Created Apr 26, 2017
            
              
                A small sample of various types of plankton from the training data
              
          
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## validation_data_creation.ipynb

      
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                crikeli
                / validation_data_creation.ipynb
            
            
              Created Apr 26, 2017
            
              
                A jupyter notebook gist for validation data creation
              
          
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## training_data_exploration.ipynb

      
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                crikeli
                / training_data_exploration.ipynb
            
            
              Last active Apr 27, 2017
            
              
                Exploring Training Data
              
          
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## min-char-rnn.py
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)
	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)