Udacity Predicting Student Admissions

# Imports
import numpy as np
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.optimizers import SGD
from keras.utils import np_utils

# Building the model
model = Sequential()
model.add(Dense(128, activation='sigmoid', input_shape=(6,)))
model.add(Dropout(.2))
model.add(Dense(64, activation='sigmoid'))
model.add(Dropout(.1))
model.add(Dense(32, activation='sigmoid'))
model.add(Dropout(.1))
model.add(Dense(2, activation='softmax'))

# Compiling the model
sgd = SGD(lr=0.001)
model.compile(loss = 'categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy'])
model.summary()