Programming Machine Learning

Running on Convolutions

Here is a convolutional neural network for CIFAR-10—all of it:

19_beyond/cifar10_cnn.py

import numpy as np
from keras.models import Sequential
from keras.layers import Conv2D, Dropout, Dense
from keras.layers import BatchNormalization, Flatten
from keras.optimizers import Adam
from keras.utils import to_categorical
from keras.datasets import cifar10

(X_train_raw, Y_train_raw), (X_test_raw, Y_test_raw) = cifar10.load_data()
X_train = X_train_raw / 255
X_test_all = X_test_raw / 255
X_validation, X_test = np.split(X_test_all, 2)
Y_train = to_categorical(Y_train_raw)
Y_validation, Y_test = np.split(to_categorical(Y_test_raw), 2)

model = Sequential()

model.add(Conv2D(16, ...