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목록mnist (2)
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[ML lab 11-2] MNIST 99% with CNN
[Simple CNN] import numpy as np import tensorflow as tf import random mnist = tf.keras.datasets.mnist (x_train, y_train), (x_test, y_test) = mnist.load_data() x_test = x_test / 255 x_train = x_train / 255 x_train = x_train.reshape(x_train.shape[0], 28, 28, 1) x_test = x_test.reshape(x_test.shape[0], 28, 28, 1) # one hot encode y data y_train = tf.keras.utils.to_categorical(y_train, 10) y_test = ..
[ML alb 07-2] Meet MNIST Dataset
import tensorflow as tf learning_rate = 0.001 batch_size = 100 training_epochs = 15 nb_classes = 10 # download mnist dataset mnist = tf.keras.datasets.mnist (x_train, y_train), (x_test, y_test) = mnist.load_data() # normalizing data x_train, x_test = x_train / 255.0, x_test / 255.0 # change data shape print(x_train.shape) # (60000, 28, 28) x_train = x_train.reshape(x_train.shape[0], x_train.shap..