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How to get AI/ML development, training & inference using Python & Jupyter Kit on AWS(Amazon Web Services)

This section describes how to launch and connect to AI/ML development, training & inference using Python & Jupyter Kit in Amazon Web Services (AWS).

Note: Now the AI/ML development, training & inference using Python & Jupyter kit is available with GPU Acceleration. To provision this VM with the GPU instance, please select the instance from g4dn family available on configuration page (Please see below configuration screenshot in step 2.).

  1. Open AI/ML development, training & inference using Python & Jupyter Kit offering on AWS.

/img/aws/aiml-marketplace.png

  1. Click on Continue to subscribe.
  • Login with your credentials and follow the instruction.
  • Note: After login, it will take you to the default annual contract page. If you do not want to provision the solution with annual contract then please skip this page by not selecting any values from the dropdown menus as shown below. /img/aws/stable-diffusion/annual-contract.png
  • Make sure the Total contract price is $0 and then Click on Continue to configuration button on top right corner. /img/aws/stable-diffusion/total-annual-contract.png
  • Next page will show you the details about hourly, monthly and annual pricing. If you don’t configure the annual contract, the instance get provisioned on hourly basis.
  • Select a Region where you want to launch the VM(such as US East (N.Virginia))

/img/aws/aws_vm1.png

  • Click on Continue to Launch Button.
  • Choose Action: You can launch it through EC2 or from Website.(Let’s choose Launch from website)
  • Optionally change the EC2 instance type. (This defaults to t2.large instance type, 2 vCPUs and 8 GB ram.) /img/aws/aiml-gpu-instance.png
  • Optionally change the network name and subnetwork names. Be sure that whichever network you specify has ports 22 (for ssh), 3389 (for RDP) and 80 (for http) exposed.
  • be sure to download the key-pair which is available by default, or you can create the new key-pair and download it.
  • Click on Launch. **Python AI & Machine learning Suit **will begin deploying.

  1. A summary page displays.To see this instance on EC2 Console click on EC2 Console link. /img/aws/aws_vm_created.png

  2. On the EC2 Console page, instance is up and running. To connect to this instance through putty via Windows Machine, copy the IPv4 Public IP Address

/img/aws/aws_vm_EC2Console.png

  1. Open putty, paste the IP address and browse your private key you downloaded while deploying the VM, by going to SSH- >Auth, click on Connect /img/aws/aws_vm_putty.png
    /img/aws/bitcoin_vm_putty_privatekey.png

  2. Once connected, change the password for ubuntu user using below command -

sudo passwd ubuntu

/img/aws/aws_vm_password_reset.png

  1. Now the password for ubuntu user is set, you can connect to the VM’s desktop environment from any local windows machine using RDP protocol or linux machine using Remmina.
  2. From your local windows machine, goto “start” menu, in the search box type and select “Remote desktop connection”
  3. In the “Remote Desktop connection” wizard, copy the public IP address and click connect

/img/aws/aws_rdp.png

  1. This will connect you to the VM’s desktop environment. Provide the username (e.g “ubuntu”) and the password set in the above “Reset password” step to authenticate. Click OK

/img/aws/aws_rdp_login.png

  1. Now you are connected to out of box MUJEFA environment via Windows Machine.

/img/aws/aws_rdp_desktop.png

  1. To connect using RDP via Linux machine, first note the external IP of the VM from VM details page,then from your local Linux machine, goto menu, in the search box type and select “Remmina”.

    Note: If you don’t have Remmina installed on your Linux machine, first Install Remmina as per your linux distribution.

/img/gcp/common/remmina-search.png

  1. In the “Remmina Remote Desktop Client” wizard, select the RDP option from dropdown and paste the external ip and click enter.

/img/gcp/common/remmina-external-ip.png

  1. This will connect you to the VM’s desktop environment. Provide “ubuntu” as the userid and the password set in step 6 to authenticate. Click OK

/img/gcp/common/remmina-rdp-login.png

  1. Now you are connected to out of box MUJEFA environment via Linux machine.

/img/aws/aws_rdp_desktop.png

  1. You can use the remote desktop you connected in above step for using the VM, however, more convenient and better method is to use the Jupyter/Ipython notebook which comes with the VM .

    The Notebook is available on the same public IP you used for remote desktop and accessible via any browser. Just open the browser and type the public IP address and you will get below screen for login.

    The Jupyter Notebook is configured with the ubuntu as an admin user. Login with ubuntu as username and use a strong password & note it down somewhere, since this will be the password for the admin user account from now on.

    Note: Make sure you use “http” and not “https” in the url

/img/aws/aws_jupyterhub_login.png

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