Jupyter Notebook 3.0.5

Jupyter Notebook is a web-based interactive environment for your code and data. Its last generation - JupyterLab - supports a wide range of data science, machine learning and computing workflows. It can be used with various runtimes (kernels): Python, R, etc.

With Puzl you can get your Jupyter Notebook in a cloud, ready in just a few clicks. You can also add GPU(s) and choose from a variety of ready-to-go environments (Docker images) containing CUDA and popular AI/ML tools. As usual in Puzl, you can flexibly configure CPU and RAM requests for your app. You're paying only for resources actually utilized by your Jupyter Notebook and not for excess infrastructure like in the case with virtual machines.

Click the 'Install' button at the top of this page and fill in the form:

1. Password - you will use it to access your Jupyter Notebook interface after installation.
2. Environment (Docker Image) - you can choose either from a selection of Docker Images, provided by Puzl for your convenience, or enter your own Docker Image from hub.docker.com.
3. Interface - choose between classic Jupyter Notebook and the next-generation JupyterLab. JupyterLab caters much more features and can be powered up with a set of widgets.
4. NVMe based persistent volume - it will store datasets and the results of your work. You may create a new Volume or pick from the existing ones.

On your Jupyter Notebook page find section Access and click on the link provided at the top of the section. Your Jupyter Notebook app will be opened in a new tab. To access the interface you will need a password, which you have specified during the installation. You can find this password below the URL in the Access section.

To check resources, in your Jupyter Notebook open Terminal and run:

Check GPU

nvidia-smi

Check data on your Volume

ls -l