🎨 Add figure showing xbatcher's features for slicing n-dim arrays (#8)

Illustration of xbatcher's features of slicing multi-dimensional arrays on-the-fly with named variables, useful for e.g. time-series or multi-variate oceanography / climate model outputs. Diagram on the left shows how a datacube is sliced, and code block on the right shows how regular slicing code compares to xbatcher.

At the bottom, more features are mentioned such as lazy loading, xarray acessors, and the experiment cache mechanism. Also mentioned upcoming roadmap like shuffling/sampling utilities and async loading of batches.

README.md

@@ -38,6 +38,7 @@ about the challenges and ideas on scaling machine learning in the geosciences
 with the [Pangeo ML Working Group](https://pangeo.io/meeting-notes.html#working-group-meetings).
 
 [![NVIDIA GPUDirect Storage schematic](https://github.com/weiji14/foss4g2023oceania/assets/23487320/b339605a-492b-4c5c-8a06-b14ebcd258b7)](https://github.com/weiji14/foss4g2023oceania/pull/6)
+[![xbatcher n-dimensional slicing](https://github.com/weiji14/foss4g2023oceania/assets/23487320/38af26ca-83ea-4798-be7f-95608ad56df0)](https://github.com/weiji14/foss4g2023oceania/pull/8)
 
 # Getting started
 

figures/README.md

@@ -6,6 +6,7 @@ Folder to store all the figures used in the presentation.
 
 - [Pangeo ML Ecosystem 2023 diagram](foss4g2023oceania_pangeo_ml_talk.excalidraw) | https://excalidraw.com/#json=Z0T6mFgNZnFSjN3rs349O,YdPkNNwey7rS5OtWgvSkyQ
 - [NVIDIA GPU Direct Storage](nvidia_gpu_direct_storage.excalidraw) | https://excalidraw.com/#json=PBEuODqMxdJFVxGrgLzkP,ZAGNmAF2OJmxeq_nIDbPEA
+- [xbatcher n-dimensional slicing](xbatcher_ndim_slicing.excalidraw) | https://excalidraw.com/#json=4iuB5hMt9ihbLNrN8Pirw,Ktfz9P8oHqQS5IJrBzoC8A
 
 ## Logos