Like every first app we should start with something super simple that gives us an idea about the whole methodology.
Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.
A layer of neurons in a neural network
A mathematical way of measuring how wrong your predictions are
An algorithm to find parameter values which correspond to minimum value of loss function
It contains one layer with one neuron.
# initialize the modelmodel = Sequential()# add a layer with one unit and set the dimension of inputmodel.add(Dense(units=1, input_shape=))# set functional properties and compile the modelmodel.compile(optimizer='sgd', loss='mean_squared_error')
After building out neural network we can feed it with our sample data 😋
xs = np.array([-1.0, 0.0, 1.0, 2.0, 3.0, 4.0], dtype=float)ys = np.array([-3.0, -1.0, 1.0, 3.0, 5.0, 7.0], dtype=float)
Then we have to start training process 🚀
model.fit(xs, ys, epochs=500)
Every thing is done 😎 ! Now we can test our neural network with new data 🎉