Moves estimator getting started docs into programmer's guide.

Update path references and magic links.
Remove getting started with estimators doc.
Add redirects.

PiperOrigin-RevId: 197826223

4 files changed, 8 insertions, 8 deletions

diff --git a/tensorflow/docs_src/tutorials/kernel_methods.md b/tensorflow/docs_src/tutorials/kernel_methods.md
index 73e5c51057..205e2a2d2c 100644
--- a/tensorflow/docs_src/tutorials/kernel_methods.md
+++ b/tensorflow/docs_src/tutorials/kernel_methods.md
@@ -53,7 +53,7 @@ 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
-@{$get_started/premade_estimators#create_input_functions$this section on input functions}.
+@{$premade_estimators#create_input_functions$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
diff --git a/tensorflow/docs_src/tutorials/layers.md b/tensorflow/docs_src/tutorials/layers.md
index 37cd2bb139..ead5a636b9 100644
--- a/tensorflow/docs_src/tutorials/layers.md
+++ b/tensorflow/docs_src/tutorials/layers.md
@@ -190,7 +190,7 @@ def cnn_model_fn(features, labels, mode):
 The following sections (with headings corresponding to each code block above)
 dive deeper into the `tf.layers` code used to create each layer, as well as how
 to calculate loss, configure the training op, and generate predictions. If
-you're already experienced with CNNs and @{$get_started/custom_estimators$TensorFlow `Estimator`s},
+you're already experienced with CNNs and @{$custom_estimators$TensorFlow `Estimator`s},
 and find the above code intuitive, you may want to skim these sections or just
 skip ahead to ["Training and Evaluating the CNN MNIST Classifier"](#train_eval_mnist).
 
@@ -535,8 +535,8 @@ if mode == tf.estimator.ModeKeys.TRAIN:
 ```
 
 > Note: For a more in-depth look at configuring training ops for Estimator model
-> functions, see @{$get_started/custom_estimators#defining-the-training-op-for-the-model$"Defining the training op for the model"}
-> in the @{$get_started/custom_estimators$"Creating Estimations in tf.estimator"} tutorial.
+> functions, see @{$custom_estimators#defining-the-training-op-for-the-model$"Defining the training op for the model"}
+> in the @{$custom_estimators$"Creating Estimations in tf.estimator"} tutorial.
 
 
 ### Add evaluation metrics
@@ -601,7 +601,7 @@ be saved (here, we specify the temp directory `/tmp/mnist_convnet_model`, but
 feel free to change to another directory of your choice).
 
 > Note: For an in-depth walkthrough of the TensorFlow `Estimator` API, see the
-> tutorial @{$get_started/custom_estimators$"Creating Estimators in tf.estimator."}
+> tutorial @{$custom_estimators$"Creating Estimators in tf.estimator."}
 
 ### Set Up a Logging Hook {#set_up_a_logging_hook}
 
@@ -720,7 +720,7 @@ Here, we've achieved an accuracy of 97.3% on our test data set.
 To learn more about TensorFlow Estimators and CNNs in TensorFlow, see the
 following resources:
 
-*   @{$get_started/custom_estimators$Creating Estimators in tf.estimator}
+*   @{$custom_estimators$Creating Estimators in tf.estimator}
     provides an introduction to the TensorFlow Estimator API. It walks through
     configuring an Estimator, writing a model function, calculating loss, and
     defining a training op.
diff --git a/tensorflow/docs_src/tutorials/linear.md b/tensorflow/docs_src/tutorials/linear.md
index 265ded877d..3f247ade26 100644
--- a/tensorflow/docs_src/tutorials/linear.md
+++ b/tensorflow/docs_src/tutorials/linear.md
@@ -17,7 +17,7 @@ tutorial walks through the code in greater detail.
 
 To understand this overview it will help to have some familiarity
 with basic machine learning concepts, and also with
-@{$get_started/premade_estimators$Estimators}.
+@{$premade_estimators$Estimators}.
 
 [TOC]
 
diff --git a/tensorflow/docs_src/tutorials/recurrent_quickdraw.md b/tensorflow/docs_src/tutorials/recurrent_quickdraw.md
index 5d83fbe2a3..1afd861738 100644
--- a/tensorflow/docs_src/tutorials/recurrent_quickdraw.md
+++ b/tensorflow/docs_src/tutorials/recurrent_quickdraw.md
@@ -220,7 +220,7 @@ length 2.
 ### Defining the model
 
 To define the model we create a new `Estimator`. If you want to read more about
-estimators, we recommend @{$get_started/custom_estimators$this tutorial}.
+estimators, we recommend @{$custom_estimators$this tutorial}.
 
 To build the model, we: