Update info about images by b-data (#2330)

README.md

@@ -165,6 +165,14 @@ to indicate the copyright and license terms:
 
 ## Alternatives
 
+- [b-data](https://github.com/b-data)'s JupyterLab docker stacks - For
+  [R](https://github.com/b-data/jupyterlab-r-docker-stack),
+  [Python](https://github.com/b-data/jupyterlab-python-docker-stack),
+  [MAX/Mojo](https://github.com/b-data/jupyterlab-mojo-docker-stack) and
+  [Julia](https://github.com/b-data/jupyterlab-julia-docker-stack).
+  With [code-server](https://github.com/coder/code-server) next to JupyterLab.
+  Just Python – no [Conda](https://github.com/conda/conda) /
+  [Mamba](https://github.com/mamba-org/mamba).
 - [rocker/binder](https://rocker-project.org/images/versioned/binder.html) -
   From the R focused [rocker-project](https://rocker-project.org),
   lets you run both RStudio and Jupyter either standalone or in a JupyterHub

docs/using/selecting.md

@@ -338,7 +338,7 @@ See the [contributing guide](../contributing/stacks.md) for information about ho
 | [GPU-Jupyter][gpu]                | Power of your NVIDIA GPU and GPU calculations using Tensorflow and Pytorch in collaborative notebooks. This is done by generating a Dockerfile that consists of the **nvidia/cuda** base image, the well-maintained **docker-stacks** that is integrated as a submodule, and GPU-able libraries like **Tensorflow**, **Keras** and **PyTorch** on top of it. |
 | [myLab TH Lübeck Images][gpu_thl] | Images based on the **jupyter/docker-stacks**, built and maintained at the [myLab TH Lübeck][gpu_mylab] using build scripts similar to iot-salzburg. Several images include GPU libraries.                                                                                                                                                                   |
 | [PRP-GPU][prp_gpu]                | PRP (Pacific Research Platform) maintained [registry][prp_reg] for jupyter stack based on NVIDIA CUDA-enabled image. Added the PRP image with Pytorch and some other Python packages and GUI Desktop notebook based on <https://github.com/jupyterhub/jupyter-remote-desktop-proxy>.                                                                         |
-| [b-data][b-data]                  | GPU accelerated, multi-arch (`linux/amd64`, `linux/arm64/v8`) docker images for [R][r_cuda], [Python][python_cuda] and [Julia][julia_cuda]. Derived from nvidia/cuda `devel`-flavored images, including TensortRT and TensorRT plugin libraries. With [code-server][code-server] next to JupyterLab. Just Python – no [Conda][conda]/[Mamba][mamba].         |
+| [b-data][b-data]                  | GPU accelerated, multi-arch (`linux/amd64`, `linux/arm64/v8`) Docker images for [R][r_cuda], [Python][python_cuda] , [MAX][max_cuda] and [Julia][julia_cuda]. Derived from nvidia/cuda `devel`-flavored images. With [code-server][code-server] next to JupyterLab. Just Python – no [Conda][conda] / [Mamba][mamba].                                        |
 
 [gpu]: https://github.com/iot-salzburg/gpu-jupyter
 [gpu_thl]: https://hub.docker.com/r/hanseware/jlab-images
@@ -348,6 +348,7 @@ See the [contributing guide](../contributing/stacks.md) for information about ho
 [b-data]: https://github.com/b-data
 [r_cuda]: https://github.com/b-data/jupyterlab-r-docker-stack/blob/main/CUDA.md
 [python_cuda]: https://github.com/b-data/jupyterlab-python-docker-stack/blob/main/CUDA.md
+[max_cuda]: https://github.com/b-data/jupyterlab-mojo-docker-stack/blob/main/CUDA.md
 [julia_cuda]: https://github.com/b-data/jupyterlab-julia-docker-stack/blob/main/CUDA.md
 [code-server]: https://github.com/coder/code-server
 [conda]: https://github.com/conda/conda