Orca: Document polishing (#6382)

* fix: delete redundant quick examples.

* feat: add How-to Guides with use cases.

* fix: _toc.yml

* fix: fix typo.

* fix: fix typo and file location.

* fix: add quickstarts to _toc.yml

docs/readthedocs/source/_toc.yml

@@ -39,15 +39,22 @@ subtrees:
                 - file: doc/Orca/Overview/distributed-tuning
                 - file: doc/Orca/Overview/ray
           - file: doc/Orca/QuickStart/index
-            title: "Quick Examples"
+            title: "Quickstarts"
             subtrees:
               - entries:
-                - file: doc/UseCase/spark-dataframe
+                - file: doc/Orca/Quickstart/orca-tf-quickstart
-                - file: doc/UseCase/xshards-pandas
+                - file: doc/Orca/Quickstart/orca-tf2keras-quickstart
-                - file: doc/Orca/QuickStart/ray-quickstart
+                - file: doc/Orca/Quickstart/orca-keras-quickstart
-                - file: doc/Orca/QuickStart/orca-pytorch-distributed-quickstart
+                - file: doc/Orca/Quickstart/orca-pytorch-quickstart
-                - file: doc/Orca/QuickStart/orca-autoestimator-pytorch-quickstart
+                - file: doc/Orca/Quickstart/ray-quickstart
-                - file: doc/Orca/QuickStart/orca-autoxgboost-quickstart
+          - file: doc/Orca/Howto/index
+            title: "How-to Guides"
+            subtrees:
+              - entries:
+                - file: doc/Orca/Howto/spark-dataframe
+                - file: doc/Orca/Howto/xshards-pandas
+                - file: doc/Orca/Howto/orca-autoestimator-pytorch-quickstart
+                - file: doc/Orca/Howto/orca-autoxgboost-quickstart
           - file: doc/Orca/Tutorial/index
             title: "Tutorials"
             subtrees:

docs/readthedocs/source/doc/Orca/Howto/index.rst

@@ -0,0 +1,7 @@
+Orca How-to Guides
+=========================
+
+* `Use Spark DataFrames for Deep Learning <spark-dataframe.html>`__
+* `Use Distributed Pandas for Deep Learning <xshards-pandas.html>`__
+* `Enable AutoML for PyTorch <orca-autoestimator-pytorch-quickstart.html>`__
+* `Use AutoXGBoost to auto-tune XGBoost parameters <orca-autoxgboost-quickstart.html>`__

docs/readthedocs/source/doc/Orca/Howto/spark-dataframe.md

@@ -6,7 +6,7 @@
 
 ---
 
-**In this guide we will describe how to use Apache Spark Dataframes to scale-out data processing for distribtued deep learning.**
+**In this guide we will describe how to use Apache Spark Dataframes to scale-out data processing for distributed deep learning.**
 
 The dataset used in this guide is [movielens-1M](https://grouplens.org/datasets/movielens/1m/), which contains 1 million ratings of 5 levels from 6000 users on 4000 movies. We will read the data into Spark Dataframe and directly use the Spark Dataframe as the input to the distributed training.
 

docs/readthedocs/source/doc/Orca/Howto/xshards-pandas.md

@@ -6,7 +6,7 @@
 
 ---
 
-**In this guide we will describe how to use [XShards](../Orca/Overview/data-parallel-processing.md) to scale-out Pandas data processing for distribtued deep learning.** 
+**In this guide we will describe how to use [XShards](../Orca/Overview/data-parallel-processing.md) to scale-out Pandas data processing for distributed deep learning.** 
 
 ### 1. Read input data into XShards of Pandas DataFrame