January 2018
Beginner to intermediate
284 pages
8h 35m
English
Forward propagation is basically calculating the input data multiplied by the networks’ weight plus the offset, and then going through the activation function to the next layer:

An example code block using TensorFlow can be written as follows:
# dimension variablesdim_in = 2 dim_middle = 5dim_out = 1# declare network variablesa_0 = tf.placeholder(tf.float32, [None, dim_in])y = tf.placeholder(tf.float32, [None, dim_out])w_1 = tf.Variable(tf.random_normal([dim_in, dim_middle]))b_1 = tf.Variable(tf.random_normal([dim_middle]))w_2 = tf.Variable(tf.random_normal([dim_middle, dim_out]))b_2 = tf.Variable(tf.random_normal([dim_out])) ...
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