Typo fixes in the documentation

docs/en_US/CommunitySharings/community_sharings.rst

@@ -9,8 +9,8 @@ In addtion to the official tutorilas and examples, we encourage community contri
 
     NNI in Recommenders <RecommendersSvd>
     Automatically tuning SPTAG with NNI <SptagAutoTune>
-    Neural Architecture Search Comparison <NasComparision>
-    Hyper-parameter Tuning Algorithm Comparsion <HpoComparision>
+    Neural Architecture Search Comparison <NasComparison>
+    Hyper-parameter Tuning Algorithm Comparison <HpoComparison>
     Parallelizing Optimization for TPE <ParallelizingTpeSearch>
     Automatically tune systems with NNI <TuningSystems>
     NNI review article from Zhihu: - By Garvin Li <NNI_AutoFeatureEng>

docs/en_US/Release.md

@@ -139,7 +139,7 @@
 * [BNN Quantizer](https://github.com/microsoft/nni/blob/v1.3/docs/en_US/Compressor/Quantizer.md#bnn-quantizer)
 #### Training Service
 * NFS Support for PAI
-    
+
     Instead of using HDFS as default storage, since OpenPAI v0.11, OpenPAI can have NFS or AzureBlob or other storage as default storage. In this release, NNI extended the support for this recent change made by OpenPAI, and could integrate with OpenPAI v0.11 or later version with various default storage.
 
 * Kubeflow update adoption
@@ -273,11 +273,11 @@
 ### Major Features
 * General NAS programming interface
     * Add `enas-mode`  and `oneshot-mode` for NAS interface: [PR #1201](https://github.com/microsoft/nni/pull/1201#issue-291094510)
-* [Gaussian Process Tuner with Matern kernel](Tuner/GPTuner.md) 
+* [Gaussian Process Tuner with Matern kernel](Tuner/GPTuner.md)
 
 * (deprecated) Multiphase experiment supports
     * Added new training service support for multiphase experiment: PAI mode supports multiphase experiment since v0.9.
-    * Added multiphase capability for the following builtin tuners: 
+    * Added multiphase capability for the following builtin tuners:
         * TPE, Random Search, Anneal, Naïve Evolution, SMAC, Network Morphism, Metis Tuner.
 
 * Web Portal
@@ -326,8 +326,8 @@
 * Fix bug of table entries
 * Nested search space refinement
 * Refine 'randint' type and support lower bound
-* [Comparison of different hyper-parameter tuning algorithm](CommunitySharings/HpoComparision.md)
-* [Comparison of NAS algorithm](CommunitySharings/NasComparision.md)
+* [Comparison of different hyper-parameter tuning algorithm](CommunitySharings/HpoComparison.md)
+* [Comparison of NAS algorithm](CommunitySharings/NasComparison.md)
 * [NNI practice on Recommenders](CommunitySharings/RecommendersSvd.md)
 
 ## Release 0.7 - 4/29/2018

docs/en_US/Tuner/BuiltinTuner.md

@@ -2,7 +2,7 @@
 
 NNI provides state-of-the-art tuning algorithms as part of our built-in tuners and makes them easy to use. Below is the brief summary of NNI's current built-in tuners:
 
-Note: Click the **Tuner's name** to get the Tuner's installation requirements, suggested scenario, and an example configuration. A link for a detailed description of each algorithm is located at the end of the suggested scenario for each tuner. Here is an [article](../CommunitySharings/HpoComparision.md) comparing different Tuners on several problems.
+Note: Click the **Tuner's name** to get the Tuner's installation requirements, suggested scenario, and an example configuration. A link for a detailed description of each algorithm is located at the end of the suggested scenario for each tuner. Here is an [article](../CommunitySharings/HpoComparison.md) comparing different Tuners on several problems.
 
 Currently, we support the following algorithms:
 
@@ -218,7 +218,7 @@ The search space file should include the high-level key `combine_params`. The ty
 
 **Suggested scenario**
 
-Note that the only acceptable types within the search space are `choice`, `quniform`, and `randint`. 
+Note that the only acceptable types within the search space are `choice`, `quniform`, and `randint`.
 
 This is suggested when the search space is small. It's suggested when it is feasible to exhaustively sweep the whole search space. [Detailed Description](./GridsearchTuner.md)
 
@@ -388,7 +388,7 @@ As a strategy in a Sequential Model-based Global Optimization (SMBO) algorithm,
 **classArgs Requirements:**
 
 * **optimize_mode** (*'maximize' or 'minimize', optional, default = 'maximize'*) - If 'maximize', the tuner will try to maximize metrics. If 'minimize', the tuner will try to minimize metrics.
-* **utility** (*'ei', 'ucb' or 'poi', optional, default = 'ei'*) - The utility function (acquisition function). 'ei', 'ucb', and 'poi' correspond to 'Expected Improvement', 'Upper Confidence Bound', and 'Probability of Improvement', respectively. 
+* **utility** (*'ei', 'ucb' or 'poi', optional, default = 'ei'*) - The utility function (acquisition function). 'ei', 'ucb', and 'poi' correspond to 'Expected Improvement', 'Upper Confidence Bound', and 'Probability of Improvement', respectively.
 * **kappa** (*float, optional, default = 5*) - Used by the 'ucb' utility function. The bigger `kappa` is, the more exploratory the tuner will be.
 * **xi** (*float, optional, default = 0*) - Used by the 'ei' and 'poi' utility functions. The bigger `xi` is, the more exploratory the tuner will be.
 * **nu** (*float, optional, default = 2.5*) - Used to specify the Matern kernel. The smaller nu, the less smooth the approximated function is.

docs/en_US/contents.rst

@@ -18,5 +18,5 @@ Neural Network Intelligence
     References <reference>
     Community Sharings <CommunitySharings/community_sharings>
     FAQ <Tutorial/FAQ>
-    How to Contribution <contribution>
-    Changelog <Release>
+    How to Contribute <contribution>
+    Changelog <Release>