Keras conv2d batchnorm

# import BatchNormalization
from keras.layers.normalization import BatchNormalization

# instantiate model
model = Sequential()

# we can think of this chunk as the input layer
model.add(Dense(64, input_dim=14, init='uniform'))
model.add(BatchNormalization())
model.add(Activation('tanh'))
model.add(Dropout(0.5))

# we can think of this chunk as the hidden layer    
model.add(Dense(64, init='uniform'))
model.add(BatchNormalization())
model.add(Activation('tanh'))
model.add(Dropout(0.5))

# we can think of this chunk as the output layer
model.add(Dense(2, init='uniform'))
model.add(BatchNormalization())
model.add(Activation('softmax'))

# setting up the optimization of our weights 
sgd = SGD(lr=0.1, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss='binary_crossentropy', optimizer=sgd)

# running the fitting
model.fit(X_train, y_train, nb_epoch=20, batch_size=16, show_accuracy=True, validation_split=0.2, verbose = 2)

Source: stackoverflow.com

Similar codes

0 vote312 views1 answer
Parquet pyspark
Python
0 vote279 views1 answer
Joint Plot Seaborn
Python
0 vote296 views1 answer
Python dataframe update if not new row
Python
-1 vote275 views1 answer
ModuleNotFoundError: No module named 'scipy'
Python
1 vote278 views1 answer
Python loop every month datetime
Python
0 vote280 views1 answer
Pycocotools python3.7
Python
1 vote288 views1 answer
Scikit learn split data set
Python
5 votes309 views1 answer
Write multiple df to excel pandas
Python
0 vote278 views1 answer
Convert 2d string array to float python
Python
42 votes282 views6 answers
If key in dictionary python
Python