For the sake of the TF beginner (this is Example aymericdamien#2 afterall), added a helpful comment about how the optimizer knows to modify W and b

ddurham2 · aymericdamien · commit c0a784a04aa0 · 2017-04-25T21:47:11.000-07:00
diff --git a/examples/2_BasicModels/linear_regression.py b/examples/2_BasicModels/linear_regression.py
@@ -38,6 +38,7 @@
 # Mean squared error
 cost = tf.reduce_sum(tf.pow(pred-Y, 2))/(2*n_samples)
 # Gradient descent
+#  Note, minimize() knows to modify W and b because Variable objects are trainable=True by default
 optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)
 
 # Initializing the variables
