Robert Haase

I just added a [CONTRIBUTING guide](https://github.com/haesleinhuepf/BioImageAnalysisNotebooks/blob/main/CONTRIBUTING.md). Let me know what you think!

> The only thing that could be considered in addition to the "short" topic notebooks are examples of complete workflows, including the post-processing part (here's an example on BBBC013: https://github.com/guiwitz/ImagingStats/blob/master/image_processing.ipynb)....

It's a very cool idea @jo-mueller! It's just tricky to implement with apoc. In very short: each OpenCL kernel (that is derived from a random forest) produces one thing: the...

Ok, that sounds to me like we build it into the PixelClassifier similar to the ProbabilityMapper so that we can use the same trained Random Forest but generate different OpenCL...

> Certainty would just be `1-Uncertainty` I'm not sure about this. If I'm certain, that's sufficient. Not being uncertain is necessary but might not be sufficient.

> * Should 1-2 examples be added with f-strings? I find them extremely useful and now favour them even with beginners over the classic `my text + str(a)` approach. Yes!...

> Just regarding Numpy in general: I also avoid going into complicated functions and just show one example like `reshape` so that students understand the logic of working with dimensions....

It's tricky indeed. Maybe we can move the basics for visualization (including napari) into a `visualization` chapter and additionally have the more advanced stuff in the `GUI` folder? I'm also...

Thanks for the feedback Peter! Ok, then it might be related to: * https://github.com/conda-forge/devbio-napari-feedstock/pull/17 CC @kevinyamauchi @jaimergp

Awesome, big thanks @jaimergp @psobolewskiPhD Also enjoy your weekend! 🌞