Update README.md

minor changes for Readme

README.md

 # Introduction 
 
 NNI (Neural Network Intelligence) is a toolkit to help users running automated machine learning experiments. 
-The tool dispatches and runs trial jobs that generated by tuning algorithms to search the best neural architecture and/or hyper-parameters at different environments (e.g. local, remote servers, Cloud).
+The tool dispatches and runs trial jobs that generated by tuning algorithms to search the best neural architecture and/or hyper-parameters at different environments (e.g. local, remote servers and cloud).
 
 ```
             AutoML experiment                                 Training Services
@@ -20,7 +20,7 @@ The tool dispatches and runs trial jobs that generated by tuning algorithms to s
 ```
 ## **Who should consider using NNI**
 * You want to try different AutoML algorithms for your training code (model) at local
-* You want to run AutoML trial jobs in different environments to speed up search (e.g. remote servers, Cloud)
+* You want to run AutoML trial jobs in different environments to speed up search (e.g. remote servers and cloud)
 * As a researcher and data scientist, you want to implement your own AutoML algorithms and compare with other algorithms
 * As a ML platform owner, you want to support AutoML in your platform
 
@@ -37,17 +37,18 @@ source ~/.bashrc
 
 ## **Quick start: run an experiment at local**
 Requirements:
-* with NNI installed on your machine.
+* NNI installed on your local machine
 
 Run the following command to create an experiment for [mnist]
 ```bash
     nnictl create --config ~/nni/examples/trials/mnist-annotation/config.yml
 ```
-This command will start the experiment and WebUI. The WebUI endpoint will be shown in the output of this command (for example, `http://localhost:8080`). Open this URL using your browsers. You can analyze your experiment through WebUI, or open trials' tensorboard. Please refer to [here](docs/GetStarted.md) for the GetStarted tutorial.
+This command will start an experiment and a WebUI. The WebUI endpoint will be shown in the output of this command (for example, `http://localhost:8080`). Open this URL in your browser. You can analyze your experiment through WebUI, or browse trials' tensorboard. 
 
+Please refer to [here](docs/GetStarted.md) for the GetStarted tutorial.
 
-# Contribute
-NNI is designed as an automatic searching framework with high extensibility. NNI has a very clear modular design. Contributing more tuner/assessor algorithms, training services, SDKs are really welcome. Please refer to [here](docs/ToContribute.md) for how to contribute.
+# Contributing
+This project welcomes contributions and suggestions, we are constructing the contribution guidelines, stay tuned =).
+
+We use [GitHub issues](https://github.com/Microsoft/nni/issues) for tracking requests and bugs.
 
-# Privacy Statement
-The [Microsoft Enterprise and Developer Privacy Statement](https://privacy.microsoft.com/en-us/privacystatement) describes the privacy statement of this software.