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Обзор библиотек для машинного обучения на Python

1573 байта добавлено, 12:26, 23 января 2019
Сверточная нейронная сеть
Y: mnist.test.labels[:<font color="blue">256</font>],
keep_prob: <font color="blue">1.0</font>}))
 
> '''Step 1, Minibatch Loss= 41724.0586, Training Accuracy= 0.156'''
'''Step 10, Minibatch Loss= 17748.7500, Training Accuracy= 0.242'''
'''Step 20, Minibatch Loss= 8307.6162, Training Accuracy= 0.578'''
'''Step 30, Minibatch Loss= 3108.5703, Training Accuracy= 0.766'''
'''Step 40, Minibatch Loss= 3273.2749, Training Accuracy= 0.727'''
'''Step 50, Minibatch Loss= 2754.2861, Training Accuracy= 0.820'''
'''Step 60, Minibatch Loss= 2467.7925, Training Accuracy= 0.844'''
'''Step 70, Minibatch Loss= 1423.8140, Training Accuracy= 0.914'''
'''Step 80, Minibatch Loss= 1651.4656, Training Accuracy= 0.875'''
'''Step 90, Minibatch Loss= 2105.9263, Training Accuracy= 0.867'''
'''Step 100, Minibatch Loss= 1153.5090, Training Accuracy= 0.867'''
'''Step 110, Minibatch Loss= 1751.1400, Training Accuracy= 0.898'''
'''Step 120, Minibatch Loss= 1446.2119, Training Accuracy= 0.922'''
'''Step 130, Minibatch Loss= 1403.7135, Training Accuracy= 0.859'''
'''Step 140, Minibatch Loss= 1089.7897, Training Accuracy= 0.930'''
'''Step 150, Minibatch Loss= 1147.0751, Training Accuracy= 0.898'''
'''Step 160, Minibatch Loss= 1963.3733, Training Accuracy= 0.883'''
'''Step 170, Minibatch Loss= 1544.2725, Training Accuracy= 0.859'''
'''Step 180, Minibatch Loss= 977.9219, Training Accuracy= 0.914'''
'''Step 190, Minibatch Loss= 857.7977, Training Accuracy= 0.930'''
'''Step 200, Minibatch Loss= 430.4735, Training Accuracy= 0.953'''
'''Optimization Finished!'''
'''Testing Accuracy: 0.94140625'''
==Keras==
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