Fix broken link in CommunitySharings (#1097)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* update readme

* update

* fix path

* update reference

* fix bug in config file

* update nni_arch_overview.png

* update

* update

* update

* update home page

* update default value of metis tuner

* fix broken link in CommunitySharings

* update rst

docs/en_US/BuiltinTuner.md

@@ -2,7 +2,7 @@
 
 NNI provides state-of-the-art tuning algorithm as our builtin-tuners and makes them easy to use. Below is the brief summary of NNI currently built-in Tuners:
 
-Note: Click the **Tuner's name** to get a detailed description of the algorithm, click the corresponding **Usage** to get the Tuner's installation requirements, suggested scenario and using example. Here is an [article](./Blog/HPOComparison.md) about the comparison of different Tuners on several problems.
+Note: Click the **Tuner's name** to get a detailed description of the algorithm, click the corresponding **Usage** to get the Tuner's installation requirements, suggested scenario and using example. Here is an [article](./CommunitySharings/HPOComparison.md) about the comparison of different Tuners on several problems.
 
 Currently we support the following algorithms:
 

docs/en_US/automl_practice_sharing.rst

-#################
-AutoML Practice Sharing
-#################
-
-..  toctree::
-    :maxdepth: 2
-
-    Neural Architecture Search Comparison<CommunitySharings/AutomlPracticeSharing/NasComparison>

docs/en_US/community_sharings.rst

@@ -8,4 +8,5 @@ In addtion to the official tutorilas and examples, we encourage community contri
     :maxdepth: 2
 
     NNI Practice Sharing<nni_practice_sharing>
-    AutoML Practice Sharing<automl_practice_sharing>
+    Neural Architecture Search Comparison<CommunitySharings/NasComparison>
+    Hyper-parameter Tuning Algorithm Comparsion<CommunitySharings/HpoComparison>

docs/en_US/nni_practice_sharing.rst

@@ -8,4 +8,3 @@ Sharing the practice of leveraging NNI to tune models and systems.
     :maxdepth: 2
 
     Tuning SVD of Recommenders on NNI<CommunitySharings/NniPracticeSharing/RecommendersSvd>
-    Auto-tuning AutoGBDT and RocksDB on NNI<CommunitySharings/NniPracticeSharing/HpoComparison>
\ No newline at end of file