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Note It is recommended that you refer to [Kaggle Notebooks]( which is a free online platform that allows for interactive computations and sharing of data. The following steps outline the process of deploying the machine learning model on the AWS Cloud: * Activate the Data pipeline by selecting **aws_data_pipeline** from the service type drop-down. This activates all the services and components as shown in the following image: To ensure that you are using the latest version, activate the **last-updated-pipeline** flag. * The next step is to create a cluster named `EMRCluster`. * For security, select **secure cluster** under **Create a cluster with master and service accounts enabled**. Click on **create cluster** as shown in the following screenshot: Ensure that you enable the **SecureCluster** flag before you create the cluster. * Once the cluster is created, we will now proceed to create the **Master role**. Select the cluster name and the zone. Note that the role can be created using either **master.sh** or **emr_describe_role** command. * Once the **Master role** is created, we will use the `emr_create_cluster_role` command to create the **Service role**. * Next, we will be creating the **container image** for the machine learning model. Ensure that the **Image type** is set to **Codedeploy** and the **Role ARN** is set to the service role. The **Codebase** will depend on the language you are using. Once the image is created, you can refer to the following link for the documentation on how to create a container image:

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