Practical Docker: Creating your own deep learning cloud computer with Docker

• 10% Spot Discount on regular price

• Use NVIDIA GPU cloud computing at low cost

• When using a cloud computer as a server for your team, you can completely isolate each team member's work environment with Docker containers.

  
  

Learning Docker Commands

Learn how to understand and apply Docker commands using the Docker help function (Section 4) .

• docker run --help

• Using chatgpt

Create a virtual machine in Azure

Create a Linux virtual machine in the Azure Cloud and connect the local environment to the cloud virtual machine in various ways. (Section 6)

• key-based ssh (secure shell)

• rdp (remote desktop protocol) in gui mode

• Connecting to VS Code Environment via Remote Tunnel Extension

Docker for Python

Learn how to create a python analysis environment using the dev container VS Code extension (Section 7) .

Building and deploying Docker images

Docker for Python using dev containers and remote tunnel extentions allows you to use Docker without having to know the basic Docker syntax. This is a powerful advantage, but to help you understand the Docker syntax more deeply, we will walk through the process of installing the latest RStudio in addition to the Kaggle R Docker Image, covering the following (Section 8) :

• COPY and ADD

• Installing additional programs with the RUN command

• Understanding Ports Connections

• CMD and ENTRYPOINT

• ARG

Setting up a file sharing system

When connecting the local environment and the cloud, which is the goal of the lab, connecting the computing environment is not enough. It may not feel inconvenient when learning, but in order to apply the knowledge you have learned to an actual project, setting up a file sharing system is essential. We will cover the following (Section 11) :

• Create ADLS2 ( azure-data-lake-gen2 )

• Connecting ADLS2 to a Linux VM via blob mount

• Connecting ADLS2 to Windows environment via blobfuse method

• Accessing ADLS2 Directory in Windows and MAC Environments via Microsoft Azure Storage Explorer

We will cover setting up a Spark analytics environment on your personal computer using Docker Compose and ADLS2 (Section 11) .

• Conceptual understanding of Docker Compose

• Connecting ADLS2 directly to a Docker container

• Configuring the PySpark Analysis Environment

True virtualization implementation

Implementing true containerization, the goal of Docker, on Linux Server virtual machines in the Azure Cloud (Section 12)

We simulate the process of creating a server administrator and multiple users, all of whom share a common Docker Image, while completely isolating each other's Docker Container environments. This is the core of mlops.