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apache · Aug 13, 2020 · efd0a9a · efd0a9a
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diff --git a/docs/python_docs/python/tutorials/deploy/export/index.rst b/docs/python_docs/python/tutorials/deploy/export/index.rst
@@ -24,25 +24,18 @@ but you also have the option to export most models to the ONNX format.
 
 .. container:: cards
 
-   .. card::
-      :title: Export ONNX Models
-      :link: onnx.html
-
-      Export your MXNet model to the Open Neural Exchange Format
-
-   .. card::
-      :title: Save / Load Parameters
-      :link: ../../packages/gluon/blocks/save_load_params.html
-
-      Save and Load your model parameters with MXnet
-
-
    .. card::
       :title: Export with GluonCV
       :link: https://gluon-cv.mxnet.io/build/examples_deployment/export_network.html
 
       How to export models trained with MXNet GluonCV.
 
+   .. card::
+      :title: Export ONNX Models
+      :link: onnx.html
+
+      Export your MXNet model to the Open Neural Exchange Format
+
 .. toctree::
    :hidden:
    :maxdepth: 1

diff --git a/docs/python_docs/python/tutorials/deploy/index.rst b/docs/python_docs/python/tutorials/deploy/index.rst
@@ -21,36 +21,30 @@ Deployment
 The following tutorials will help you learn how to deploy MXNet on various
 platforms and in different language environments.
 
-Export_
+Export
 ------
 The following tutorials will help you learn export MXNet models.
 
 .. container:: cards
 
-   .. card::
-      :title: Export ONNX Models
-      :link: export/onnx.html
-
-      Export your MXNet model to the Open Neural Exchange Format
-
    .. card::
       :title: Export with GluonCV
       :link: https://gluon-cv.mxnet.io/build/examples_deployment/export_network.html
 
       How to export models trained with MXNet GluonCV.
 
-Inference_
+   .. card::
+      :title: Export ONNX Models
+      :link: export/onnx.html
+
+      Export your MXNet model to the Open Neural Exchange Format
+
+Inference
 ---------
 The following tutorials will help you learn how to deploy MXNet models for inference applications.
 
 .. container:: cards
 
-   .. card::
-      :title: CPP Inference
-      :link: inference/cpp.html
-
-      How to deploy MXNet C++ Models
-
    .. card::
       :title: GluonCV Models in a C++ Inference Application
       :link: https://gluon-cv.mxnet.io/build/examples_deployment/cpp_inference.html
@@ -63,7 +57,25 @@ The following tutorials will help you learn how to deploy MXNet models for infer
 
       How to use quantized GluonCV models for inference on Intel Xeon Processors to gain higher performance.
 
-Cloud_
+   .. card::
+      :title: C++
+      :link: inference/cpp.html
+
+      How to use MXNet models in a C++ environment.
+
+   .. card::
+      :title: Image Classification on Jetson
+      :link: inference/image_classification_jetson.html
+
+      Example of running a pretrained image classification model on a Jetson module.
+
+   .. card::
+      :title: Object Detection on Jetson
+      :link: https://gluon-cv.mxnet.io/build/examples_detection/demo_jetson.html
+
+      Example of running a pretrained object detection model on a Jetson module.
+
+Cloud
 -----
 The following tutorials will show you how to use MXNet on AWS.
 
@@ -89,7 +101,7 @@ The following tutorials will show you how to use MXNet on AWS.
 
    .. card::
       :title: Training with Data from S3
-      :link: https://mxnet.apache.org/api/faq/s3_integration
+      :link: /api/faq/s3_integration
 
       How to train with data from Amazon S3 buckets.
 
@@ -112,7 +124,3 @@ Security
    export/index
    inference/index
    run-on-aws/index
-
-.. _Export: export/index.html
-.. _Inference: inference/index.html
-.. _Cloud: run-on-aws/index.html
diff --git a/docs/python_docs/python/tutorials/deploy/inference/index.rst b/docs/python_docs/python/tutorials/deploy/inference/index.rst
@@ -34,24 +34,12 @@ The following tutorials will help you learn how to deploy MXNet models for infer
 
       How to use quantized GluonCV models for inference on Intel Xeon Processors to gain higher performance.
 
-
-The following tutorials will help you learn how to deploy MXNet models for inference applications.
-
-.. container:: cards
-
    .. card::
       :title: C++
       :link: cpp.html
 
       How to use MXNet models in a C++ environment.
 
-
-   .. card::
-      :title: Raspberry Pi
-      :link: wine_detector.html
-
-      Example of running a wine detector on a raspberry pi.
-
    .. card::
       :title: Image Classification on Jetson
       :link: image_classification_jetson.html

diff --git a/docs/python_docs/python/tutorials/extend/custom_layer.md b/docs/python_docs/python/tutorials/extend/custom_layer.md
diff --git a/docs/python_docs/python/tutorials/extend/index.rst b/docs/python_docs/python/tutorials/extend/index.rst
@@ -24,10 +24,16 @@ The following tutorials will help you learn how to customize MXNet.
 
    .. card::
       :title: Custom Layers for Gluon
-      :link: custom_layer.html
+      :link: ../packages/gluon/blocks/custom-layer.html
 
       How to add new layer functionality to MXNet's imperative interface.
 
+   .. card::
+      :title: Custom Loss
+      :link: ../packages/gluon/loss/custom-loss.html
+
+      A guide to implementing custom losses.
+
    .. card::
       :title: Custom Operators Using Numpy
       :link: customop.html
@@ -36,13 +42,13 @@ The following tutorials will help you learn how to customize MXNet.
 
    .. card::
       :title: New Operator Creation
-      :link: https://mxnet.apache.org/api/faq/new_op
+      :link: /api/faq/new_op
 
       How to create new MXNet operators using CustomOp (Python) or NNVM (C++).
 
    .. card::
       :title: A Beginner’s Guide to Implementing Operators in MXNet Backend
-      :link: https://mxnet.apache.org/api/faq/add_op_in_backend
+      :link: /api/faq/add_op_in_backend
 
       How to create new MXNet operators in MXNet's backend using C++.
       An example custom quadratic function op.