Untitled

gagarin_1982

Jan 17th, 2025

Never

Add comment

Not a member of Pastebin yet? Sign Up, it unlocks many cool features!

text 1.12 KB | None | 0 0

raw download clone embed print report

!pip install keras -q
!pip install tensorflow -q
from keras.datasets import fashion_mnist
from keras.layers import Dense, Input
from keras.models import Sequential
import numpy as np
def load_train():
(features_train, target_train), _ = fashion_mnist.load_data()
features_train = features_train.reshape(features_train.shape[0], 28 * 28) / 255.
return features_train, target_train
def create_model(input_shape):
model = Sequential()
model.add(Input(shape=input_shape))
model.add(Dense(64, activation='relu'))
model.add(Dense(32, activation='softmax'))
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['acc'])
return model
def train_model(model, train_data, batch_size=32, epochs=10):
features_train, target_train = train_data
model.fit(features_train, target_train, batch_size=batch_size, epochs=epochs, verbose=2, shuffle=True)
return model
features_train, target_train = load_train()
input_shape = (28 * 28,)
model = create_model(input_shape)
train_data = (features_train, target_train)
trained_model = train_model(model, train_data)

Add Comment

Please, Sign In to add comment