the 'ragged data' and 'conclusion' sections (#13)

* add ragged data

* add conclusion

* add torch_geometric and indicate which packages are optional

* start working on some ideas

* rename

* rename

* writing

* done with ragged

* done with ragged

* conclusion is done

deep-learning-intro-for-hep/00-intro.md

@@ -46,6 +46,8 @@ Make sure that you have the following packages installed with [conda](https://sc
 
 If you're using pip, see [PyTorch's documentation](https://pytorch.org/get-started/locally/) for instructions. The name `pytorch-cpu` is only for conda.
 
+The packages labeled "used in very few sections (optional)" are only used in the sections _after_ the main project, which is a tour of neural networks beyond supervised regression and classification. You only need to install these if you're working on those sections. The `torch_geometric` package is pip-only. You can get it in conda with the `pyg` package, but only in the `pyg` channel.
+
 The exercises are all small enough that you won't need a GPU, but if you want to use PyTorch with your GPU, you'll have to install the GPU drivers (only) outside of conda and then `conda install 'cuda-version>=12' pytorch pytorch-cuda`. If you're using pip, note that you have to install CUDA outside of pip.
 
 To get all of these pages in Jupyter notebook form, download the repository:

deep-learning-intro-for-hep/_toc.yml

@@ -28,4 +28,5 @@ chapters:
 - file: 22-beyond-supervised
 - file: 23-autoencoders
 - file: 24-convolutional
-- file: 25-deepsets-and-graphs
+- file: 25-ragged-data-and-graphs
+- file: xx-conclusion