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As we are starting to use Data Version Control for our own projects, we could have an optional exercise on how to use DVC with Annif.

Hi,
I have the VirtualBox version of the Annif tutorial, and have been through the mandatory exercises. I must say the tutorial is very useful and pedagogically presented!
Is there any way I can try Annif with any of my own vocabularies and data sets within that framework?
Oddrun

We could consider offering a PDF file having the (some) content of the tutorial as an alternate format beside the GitHub markdown files. It could be easier to follow, at least for self-studying.

Pandoc is mentioned as a tool for the conversion as well as markdown-book.

When NatLibFi/Annif#762 is in Annif, there could be an exercise about using the integration. Minimally just running for example

annif download-projects yso-mllm-en NatLibFi/FintoAI-data-YSO

This might be a stupid question, but how do I use the pretrained models available via API locally (either via docker or Python)? It seems that in all tutorials and instructions here the main assumption is that models are trained from scratch. I would just like to download the latest models you have available via your API and use them locally. I can use your online API (e.g., via Python), but I'd rather use faster offline solution as I have tens of thousands of documents to process.
For example, see the docker for Turku NLP neural parser (http://turkunlp.org/Turku-neural-parser-pipeline/docker.html): Just few simple steps and you can use pretained models with your own texts. I was looking for something similar for Annif.

I've just installed VirtualBox on my Windows 10 laptop, downloaded Annif-tutorial and added the Annif-tutorial image to VirtualBox, - all according to tutorial instruction video.
When trying to start the image (green arrow), I get the following error message:

Failed to open a session for the virtual machine annif-tutorial.
Not in a hypervisor partition (HVP=0) (VERR_NEM_NOT_AVAILABLE).
VT-x is disabled in the BIOS for all CPU modes (VERR_VMX_MSR_ALL_VMX_DISABLED).

Any idea what to do?

A common question in the tutorial sessions has been "how many documents do I need for training a model". We could have an optional exercise that would show how increasing --docs-limit value in training a model affects the evaluation results of the model. Also some simple way to plot the results as a learning curve would be nice.

This needs to be updated after PR NatLibFi/Annif#702

On page https://github.com/NatLibFi/Annif-tutorial/blob/master/exercises/README.md section 2 TFIDF: Link "Slides" does not work, it gives an error message 'Error rendering embedded code Invalid PDF'

Edit: The same happens with 'Slides' link on subchapter 'Algorithms' and Chapter 3 Web UI as well, probably also on other chapters.