diff --git a/NBSETUP.md b/NBSETUP.md
index b3c683b3..0501d7eb 100644
--- a/NBSETUP.md
+++ b/NBSETUP.md
@@ -1,9 +1,9 @@
 # Set up your notebook environment for Azure Machine Learning
 
-To run the notebooks in this repository use one of following options.
+To run the notebooks in this repository use one of the following options.
 
 ## **Option 1: Use Azure Notebooks**
-Azure Notebooks is a hosted Jupyter-based notebook service in the Azure cloud. Azure Machine Learning Python SDK is already pre-installed in the Azure Notebooks `Python 3.6` kernel.
+Azure Notebooks is a hosted Jupyter-based notebook service in Azure cloud. Azure Machine Learning Python SDK is already pre-installed in the Azure Notebooks `Python 3.6` kernel.
 
 1. [![Azure Notebooks](https://notebooks.azure.com/launch.png)](https://aka.ms/aml-clone-azure-notebooks)
 [Import sample notebooks ](https://aka.ms/aml-clone-azure-notebooks) into Azure Notebooks
@@ -20,7 +20,7 @@ We recommend you create a Python virtual environment ([Miniconda](https://conda.
 # install just the base SDK
 pip install azureml-sdk
 
-# clone the sample repoistory
+# clone the sample repository
 git clone https://github.com/Azure/MachineLearningNotebooks.git
 
 # below steps are optional
@@ -57,19 +57,19 @@ Please make sure you start with the [Configuration](configuration.ipynb) noteboo
 
 You need to have Docker engine installed locally and running. Open a command line window and type the following command. 
 
-__Note:__ We use version `1.0.10` below as an exmaple, but you can replace that with any available version number you like.
+__Note:__ We use version `1.0.10` below as an example, but you can replace it with any available version.
 
 ```sh
-# clone the sample repoistory
+# clone the sample repository
 git clone https://github.com/Azure/MachineLearningNotebooks.git
 
 # change current directory to the folder 
 # where Dockerfile of the specific SDK version is located.
 cd MachineLearningNotebooks/Dockerfiles/1.0.10
 
-# build a Docker image with the a name (azuremlsdk for example) 
+# build a Docker image with a name (for example, azuremlsdk) 
 # and a version number tag (1.0.10 for example).
-# this can take several minutes depending on your computer speed and network bandwidth.
+# this can take several minutes depending on your computer's speed and network bandwidth.
 docker build . -t azuremlsdk:1.0.10
 
 # launch the built Docker container which also automatically starts
@@ -77,7 +77,7 @@ docker build . -t azuremlsdk:1.0.10
 docker run -it -p 8887:8887 azuremlsdk:1.0.10
 ```
 
-Now you can point your browser to http://localhost:8887. We recommend that you start from the `configuration.ipynb` notebook at the root directory.
+Now you can point your browser to http://localhost:8887. We recommend that you start with the `configuration.ipynb` notebook at the root directory.
 
 If you need additional Azure ML SDK components, you can either modify the Docker files before you build the Docker images to add additional steps, or install them through command line in the live container after you build the Docker image. For example:
 
@@ -92,4 +92,4 @@ pip install azureml-sdk[interpret]
 pip install azureml-sdk[contrib]
 ```
 Drag and Drop
-The image will be downloaded by Fatkun
\ No newline at end of file
+The image will be downloaded by Fatkun