How to Install ML Workspace on Windows 10

In this tutorial, we will guide you through the process of installing ML Workspace on Windows 10 operating system. ML Workspace is an all-in-one web-based platform for machine learning and data science that provides users with pre-configured JupyterLab, RStudio, VS Code, and other essential tools.

Prerequisites

Before we begin, you should make sure you have the following prerequisites:

• Windows 10 operating system
• Docker Desktop installed and running
• Git installed on your computer
• 4GB or more of RAM

Steps

1. Open a Command Prompt or PowerShell terminal on your Windows 10 machine.
2. Clone the ML Workspace repository by running the following command:

git clone https://github.com/ml-tooling/ml-workspace.git

3. Navigate to the newly created ml-workspace directory:

cd ml-workspace

4. Run the following command to build the Docker image:

docker-compose build

This command will download and install all the necessary dependencies required to run ML Workspace.

5. After the build is complete, start the ML Workspace by running the following command:

docker-compose up

This command will start the containers and launch the web interface in your default browser.

6. Once the installation is complete, you will be able to access the ML Workspace interface on your local machine by opening a web browser and navigating to http://localhost:8080.

7. Here you will find a range of pre-installed tools and services, including JupyterLab, RStudio, and VS Code, which can be accessed by clicking on the relevant icon.

Congratulations! You have successfully installed ML Workspace on your Windows 10 machine. You can now start exploring the various tools and services offered to build and deploy machine learning models.

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