from keras.models import Sequential model = Sequential()
from keras.models import Sequential from keras.layers import Dense model = Sequential([ Dense(64, activation='relu', input_shape=(784,)), Dense(10, activation='softmax') ])
from keras.models import Sequential from keras.layers import Conv2D, MaxPooling2D, Flatten, Dense model = Sequential([ Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=(28,28,1)), MaxPooling2D(pool_size=(2, 2)), Flatten(), Dense(128, activation='relu'), Dense(10, activation='softmax') ])This defines a convolutional neural network with a 2D convolutional layer followed by max pooling, a flatten layer, and two fully connected layers, where the input images have a size of 28x28x1. In conclusion, the keras.models.Sequential __init__ is a method for initializing a Sequential model object in Python using the Keras library.