[딥러닝] 딥러닝 활용하기(cifar100 데이터 셋 학습하기)

 

CIFAR-100 데이터 셋 차원 살펴보기

import tensorflow as tf

mnist=tf.keras.datasets.cifar100

(X,YT),(x,yt)=mnist.load_data()

print(X.shape, YT.shape, x.shape, yt.shape)

import matplotlib.pyplot as plt

plt.imshow(X[0])
plt.show()

print(YT[0])

 

 

 

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CIFAR-100 데이터 셋 학습하기

import tensorflow as tf

mnist=tf.keras.datasets.cifar100

(X,YT),(x,yt)=mnist.load_data()
X=X.reshape(50000,32*32*3)/255
x=x.reshape(10000,32*32*3)/255

model=tf.keras.Sequential([
    tf.keras.Input(shape=(32*32*3,)),
    tf.keras.layers.Dense(512,activation='relu'),
    tf.keras.layers.Dense(100,activation='softmax')
])

model.compile(optimizer='adam',
             loss='sparse_categorical_crossentropy',
             metrics=['accuracy'])

model.fit(X,YT,epochs=20)

model.evaluate(x,yt)