Update v0.3.0 release note (#324)

update v0.3.0 release note

docs/RELEASE.md

 # Release 0.3.0 - 11/2/2018
-## Major Features
-* Support running multiple experiments simultaneously. You can run multiple experiments by specifying a unique port for each experiment:
+## NNICTL new features and updates
+* Support running multiple experiments simultaneously. 
+
+    Before v0.3, NNI only supports running single experiment once a time. After this realse, users are able to run multiple experiments simultaneously. Each experiment will require a unique port, the 1st experiment will be set to the default port as previous versions. You can specify a unique port for the rest experiments as below:
 
     ```nnictl create --port 8081 --config <config file path>```
+* Support updating max trial number.
+    use ```nnictl update --help``` to learn more. Or refer to [NNICTL Spec](https://github.com/Microsoft/nni/blob/master/docs/NNICTLDOC.md) for the fully usage of NNICTL.
 
-    You can still run the first experiment without '--port' parameter:
+## API new features and updates
+* <span style="color:red">**breaking change**</span>: nn.get_parameters() is refactored to nni.get_next_parameter. All examples of prior releases can not run on v0.3, please clone nni repo to get new examples. If you had applied NNI to your own codes, please update the API accordingly.
 
-    ```nnictl create --config <config file path>```
-* A builtin Batch Tuner which iterates all parameter combination, can be used to submit batch trial jobs.
-* nni.report_final_result(result) API supports more data types for result parameter, it can be of following types:
+* New API **nni.get_sequence_id()**. 
+    Each trial job is allocated a unique sequence number, which can be retrieved by nni.get_sequence_id() API.
+
+    ```git clone -b v0.3 https://github.com/Microsoft/nni.git```
+* **nni.report_final_result(result)** API supports more data types for result parameter. 
+    It can be of following types:
     * int
     * float
     * A python dict containing 'default' key, the value of 'default' key should be of type int or float. The dict can contain any other key value pairs.
-* Continuous Integration
-    * Switched to Azure pipelines
-* Others
-    * New nni.get_sequence_id() API. Each trial job is allocated a unique sequence number, which can be retrieved by nni.get_sequence_id() API.
-    * Download experiment result from WebUI
-    * Add trial examples using sklearn and NNI together
-    * Support updating max trial number
-    * Kaggle competition TGS Salt code as an example
-    * NNI Docker image:
 
-      ```docker pull msranni/nni:latest```
+## New tuner support
+* **Batch Tuner** which iterates all parameter combination, can be used to submit batch trial jobs.
 
-## Breaking changes
-*   <span style="color:red">API nn.get_parameters() is renamed to nni.get_next_parameter(), this is a broken change, all examples of prior releases can not run on v0.3, please clone nni repo to get new examples.</span>
+## New examples
+* A NNI Docker image for public usage:
+      ```docker pull msranni/nni:latest```
+* New trial example: [NNI Sklearn Example](https://github.com/Microsoft/nni/tree/master/examples/trials/sklearn)
+* New competition example: [Kaggle Competition TGS Salt Example](https://github.com/Microsoft/nni/tree/master/examples/trials/kaggle-tgs-salt)
     
-    ```git clone -b v0.3 https://github.com/Microsoft/nni.git```
+## Others
+* UI refactoring, refer to [WebUI doc](WebUI.md) for how to work with the new UI.
+* Continuous Integration: NNI had switched to Azure pipelines
+* [Known Issues in release 0.3.0](https://github.com/Microsoft/nni/labels/nni030knownissues).
 
-## Know issues
-[Known Issues in release 0.3.0](https://github.com/Microsoft/nni/labels/nni030knownissues).
 
 # Release 0.2.0 - 9/29/2018
 ## Major Features

docs/tutorial_1_CR_exp_local_api.md

@@ -17,7 +17,7 @@ To enable NNI API, make the following changes:
 1.2 Get predefined parameters
     Use the following code snippet: 
 
-        RECEIVED_PARAMS = nni.get_parameters()
+        RECEIVED_PARAMS = nni.get_next_parameter()
 
     to get hyper-parameters' values assigned by tuner. `RECEIVED_PARAMS` is an object, for example: