How to Install ML Workspace on EndeavourOS Latest

ML Workspace is a powerful web-based development environment for machine learning and data science. It provides a comprehensive collection of pre-installed machine learning and data science tools in a single container. If you are a data scientist or machine learning enthusiast, ML Workspace is an excellent tool for running preconfigured tools in a seamless and effortless way.

In this tutorial, we will show you how to install ML Workspace on EndeavourOS. Let's get started.

Prerequisites

Before we move forward, make sure that you have met the following requirements:

• A machine running EndeavourOS with sudo privileges.

• Docker and Docker Compose should be installed on your system. If you don't have it, please follow the official documentation to install it.

Step 1: Clone the Repository

First, you need to clone the ML Workspace repository on your system. You can do this by running the following command:

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

Once the cloning process is complete, navigate to the cloned directory using the following command:

$ cd ml-workspace

Step 2: Build the Container

In this step, we will build the container using Docker. To build the container, execute the following command in your terminal:

$ sudo docker-compose build

This process may take some time to complete, depending on your internet speed and system performance.

Step 3: Start the Container

After building the container, you can start the container using the following command:

$ sudo docker-compose up

This command will start the container, and you will see the logs on the screen.

Step 4: Access the ML Workspace

Once the container is up and running, you can access the ML Workspace in your web browser by navigating to http://localhost:8080.

You will see an interface that looks like this:

You can start using the preconfigured tools by opening them up from the interface.

Conclusion

In this tutorial, we have shown you how to install ML Workspace on EndeavourOS. You can now use the preconfigured tools to run your machine learning and data science experiments in a seamless and effortless way.

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