message: Fix several broken links in kernel method tutorials
diff: # Improving Linear Models Using Explicit Kernel Methods
  Note: This document uses a deprecated version of @{tf.estimator},
  +<<<<<<< HEAD
  which has a different interface (see `tf.contrib.learn Estimator`).
  +=======
  +which has a @{tf.contrib.learn.estimator$different interface}.
  +>>>>>>> Fix several broken links in kernel method tutorials
  It also uses other `contrib` methods whose
  @{$version_compat#not_covered$API may not be stable}.
  @@ -53,7 +57,7 @@ In order to feed data to a `tf.contrib.learn Estimator`, it is helpful to conver
  it to Tensors. For this, we will use an `input function` which adds Ops to the
  TensorFlow graph that, when executed, create mini-batches of Tensors to be used
  downstream. For more background on input functions, check
  -@{$get_started/premade_estimators#input_fn$this section on input functions}.
  +@{$get_started/premade_estimators#create_input_functions$this section on input functions}.
  In this example, we will use the `tf.train.shuffle_batch` Op which, besides
  converting numpy arrays to Tensors, allows us to specify the batch_size and
  whether to randomize the input every time the input_fn Ops are executed
  