installation.md

-## Installation
+## Installation using Anaconda
 
 In this section, we provide instructions on how the user can build the python Flask server of the Forecasting Toolbox from scratch, using the Anaconda virtual environment. The Forecasting Toolbox is developed to run on Unix and Windows systems with python 3.6.* innstalled. We suggest installing python via the Anaconda distribution as it provides an easy way to create a virtual environment and install dependencies. The configuration steps needed, are described below:
 
@@ -21,9 +21,9 @@ conda install -c saravji pmdarima
 ```
 - **Step 4**: To start the server, use the command promt inside the active environment and execute the commands described in section [Run Server](run server).
 
-## Installation using Docker
+## Installation using Docker Build
 
-In this section, we provide instructions on how the user can build a new Docker Image that contains the python Flask app and the Conda environment of the of the Forecasting Toolbox. We highly recommend the users to select this way of installing the SDK4ED Forecasting Toolbox, as it constitutes the easiest way.
+In this section, we provide instructions on how the user can build from scratch a new Docker Image that contains the python Flask app and the Conda environment of the of the Forecasting Toolbox.
 
 - **Step 1**: Download and install [Docker](https://www.docker.com/)
 - **Step 2**: Clone the latest Forecasting Toolbox version and navigate to the home directory. You should see a *DockerFile* and a *environment.yml* file, which contains the Conda environment dependencies. 
@@ -36,4 +36,20 @@ This command will result in the creation of a Docker Image named *forecaster_too
 sudo docker run -it --name forecaster-toolbox-test -p 5000:5000 forecaster_toolbox
 ``` 
 This command will generate and run a Docker Container named *forecaster-toolbox-test* in interactive session mode, i.e. it will open a command promt inside the Container. 
-- **Step 4**: To start the server, use the command promt inside the running Container and execute the commands described in section [Run Server](run server).
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+- **Step 4**: To start the server, use the command promt inside the running Container and execute the commands described in section [Run Server](run server).
+
+## Installation using a pre-built Docker Image from DockerHub
+
+Alternatively, you can skip the process of building the Forecasting Toolbox image from scratch by using the pre-existing image available on [DockerHub](https://hub.docker.com/r/tsoukj/forecaster_toolbox). We highly recommend new users to select this option of installing the SDK4ED Forecasting Toolbox, as it constitutes the easiest way.
+
+- **Step 1**: Download and install [Docker](https://www.docker.com/)
+- **Step 2**: Open cmd and execute the following command:
+```bash
+docker pull tsoukj/forecaster_toolbox
+```
+This command will download the latest Docker Image named *forecaster_toolbox* from DockerHub. In order to create a Docker Container from this image, execute the following command:
+```bash
+sudo docker run -it --name forecaster-toolbox-test -p 5000:5000 forecaster_toolbox
+``` 
+This command will generate and run a Docker Container named *forecaster-toolbox-test* in interactive session mode, i.e. it will open a command promt inside the Container. 
+- **Step 3**: To start the server, use the command promt inside the running Container and execute the commands described in section [Run Server](run server).
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