Forward prop in tensorflow

1.how to build layers

1. Manually（1x3matrix）

   点击查看代码

   x = np.arrat([200.0, 17.0])
   layer_1 = Dense(units=3, activation='sigmoid')
   a1 = layer_1(x)
   layer_2 = Dense(units=1, activation='sigmoid')
   a2 = layer_2(a1)
   #a1&a2 are stored in TensorFlow format. Run this to convert it to NumPy: a1.numpy().
   

2. Automatically

   点击查看代码

   layer_1 = Dense(units=3, activation='sigmoid')
   layer_2 = Dense(units=1, activation='sigmoid')
   model = Sequential([layer_1, layer_2])
   

3. Compile the model

   点击查看代码

   model.compile(...)
   x = np.array([...])
   y = np.array([...])
   model.fit(x,y)
   model.predict(x_test)
   

4. All

   点击查看代码

   model = Sequential([Dense(units=25, activation='sigmoid'),Dense(units=15, activation='sigmoid'),Dense(units=1, activation='sigmoid')])
   model.compile(...)
   x = np.array([...])
   y = np.array([...])
   model.fit(x,y)
   model.predict(x_test)