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interactive_tutorials's Introduction

ArangoDB Interactive Tutorials

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Here you will find tutorials and interactive notebooks for ArangoDB features. These notebooks allow you to learn about ArangoDB concepts and features without the need to install or sign up for anything. Each notebook uses a free temporary tutorial database that lets you focus on all the cool things ArangoDB has to offer.

Learn

There are a few sections for getting started with Interactive Tutorials:

  • Machine Learning: Links to the various ArangoDB machine-learning projects and learning content.
  • ArangoDB: The interactive tutorials maintained in this repo that cover all aspects of ArangoDB.
  • Community Notebooks: Amazing submissions from the community!
  • Workshop Repositories: Links to the repositories associated with ArangoDB workshops.
  • Feedback: Feel free to leave us feedback.
  • Contribute: Learn how to contribute your own learning content.

Machine Learning

In addition to the notebooks listed in the following section, we have example machine learning notebooks with ArangoML, including:

ArangoDB

These notebooks are interactive and take the hands-on learning approach, so feel free to play around and change things. Each notebook provides an intoduction to its covered topics along with the ability to see it in action immediately.

Most notebooks were developed with Google Colab in mind and many have an button.

The following links will open the notebooks directly in Google Colab, the source files are located in the notebooks folder.

Community Notebooks

If you have a use case you would like to show off or even a quick tutorial for an ArangoDB feature, this would be very helpful to the ArangoDB community. It's easy to get started with our Template.ipynb, which shows you how to use the tutorial endpoint in your notebooks. When ready, open a PR with your submission, and we will add it to the list, share it with the community, and be eternally grateful.

Notebooks:

Workshop Repositories

The following is a list of workshops given that cover topics related to ArangoDB. If you would like to add a workshop that might be interesting to the ArangoDB community, please add it to the list and open a pull request.

Feedback

Do you have some topics you would like to see a notebook for? Well, read on to the contribute section for details on how to submit a notebook of your own.

You can also always drop us a line at [email protected] or join us on our community Slack channel.

Contribute

Do you have a great idea for a notebook?

Did you see something you think could be better?

Have a cool project that uses ArangoDB that you would like to share with the community?

Notebooks

Make a notebook of your own!

We have provided a template that will help you quickly get started creating a notebook that can also generate a temporary database for fellow learners.

Just open up the Template.ipynb file to learn more about what it takes to get started or you can use the Template_basic.ipynb file to get a simple notebook with only the connection code done for you.

Once your notebook is ready for the world to see, you can place it in the community_notebooks folder and create a pull request.

Workshops

If you have a workshop repository that you would like added to the list, add it to the Workshop Repositories section and open a pull request.

Something Else?

Open an issue or pull request with your suggestion. You can also drop us a line at [email protected] or join us on our community Slack channel.

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interactive_tutorials's Issues

Transductive Approaches

Hi, thanks for your tutorial!

I am confused by something you mentioned in it. You said GCN is transductive, in contrast to GraphSage, which is inductive.
Later you mentioned one of the shortcomings of the transductive methods as not being able to use node features.
I was wondering if this statement is correct since GCN takes adjacency matrix along with feature matrix as its input and the features will be the hidden representations at level 0, right?

I would be grateful if you address my confustion.
Thanks!

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