HUSEIN ZOLKEPLI huseinzol05

## time-comparison-numpy-cupy.ipynb

      
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              February 23, 2018 11:30
            
              
                time comparison Numpy and Cupy for feed-forward neural network on Iris dataset
              
          
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## loop-cnn.ipynb

      
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                / loop-cnn.ipynb
            
            
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              February 24, 2018 12:30
            
              
                loop 2d convolution process
              
          
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## conv2d-mnist.ipynb

      
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                / conv2d-mnist.ipynb
            
            
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              March 4, 2018 09:56
            
              
                convolutional neural network pure numpy including back-propagation
              
          
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## atrous2d-loop-backpropagation.ipynb

      
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                huseinzol05
                / atrous2d-loop-backpropagation.ipynb
            
            
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              March 5, 2018 08:32
            
              
                atrous2d loop based with back-propagation using numpy
              
          
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## maxpooling2d.ipynb

      
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                / maxpooling2d.ipynb
            
            
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              March 6, 2018 14:54
            
              
                max pooling 2d numpy with back-propagation
              
          
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## avgpooling2d.ipynb

      
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              March 6, 2018 15:03
            
              
                average pooling 2d numpy with back-propagation
              
          
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## query-mysql.py
query = r'"najib" OR "mahathir"'

def query_to_mysql(query, column_name):
    query = query.replace(r'"', "'")
    splitted = query.split("'")
    for i in range(len(splitted)):
        if splitted[i].find('AND') < 0 and splitted[i].find('OR') < 0 and len(splitted[i])>2:
            splitted[i] = column_name + ' like \'%'+splitted[i]+'%\''
    return ' '+''.join(splitted)


## parse-date-google.py
string = '2015年5月17日'
import re

re.findall("[-+]?[.]?[\d]+(?:,\d\d\d)*[\.]?\d*(?:[eE][-+]?\d+)?", string)
# ['2015', '5', '17']

## spatialdropout.py
import tensorflow as tf

x = tf.random_normal((32, 4, 10))
out = tf.layers.dropout(x, 0.5, noise_shape=[x.shape[0], x.shape[1], tf.constant(1)]))

## residualblock.py
import tensorflow as tf

x = tf.random_normal((32, 4, 10))
x_copy = x
size = 16
kernel = 4
rate = 2
pad_len = (kernel - 1) * rate
x = tf.pad(x, [[0, 0], [pad_len, 0], [0, 0]])
x = tf.layers.conv1d(x, size, 4, dilation_rate=rate)
	query = r'"najib" OR "mahathir"'

	def query_to_mysql(query, column_name):
	query = query.replace(r'"', "'")
	splitted = query.split("'")
	for i in range(len(splitted)):
	if splitted[i].find('AND') < 0 and splitted[i].find('OR') < 0 and len(splitted[i])>2:
	splitted[i] = column_name + ' like \'%'+splitted[i]+'%\''
	return ' '+''.join(splitted)
	string = '2015年5月17日'
	import re

	re.findall("[-+]?[.]?[\d]+(?:,\d\d\d)[\.]?\d(?:[eE][-+]?\d+)?", string)
	# ['2015', '5', '17']
	import tensorflow as tf

	x = tf.random_normal((32, 4, 10))
	out = tf.layers.dropout(x, 0.5, noise_shape=[x.shape[0], x.shape[1], tf.constant(1)]))
	import tensorflow as tf

	x = tf.random_normal((32, 4, 10))
	x_copy = x
	size = 16
	kernel = 4
	rate = 2
	pad_len = (kernel - 1) * rate
	x = tf.pad(x, [[0, 0], [pad_len, 0], [0, 0]])
	x = tf.layers.conv1d(x, size, 4, dilation_rate=rate)