diff --git a/doc.zih.tu-dresden.de/docs/software/tensorboard.md b/doc.zih.tu-dresden.de/docs/software/tensorboard.md
index 0dcaf39add46347d93ab94ca7e6f44b9b7903fd6..d12258cd597aa963785b6f7fcb45481a34bdd2e9 100644
--- a/doc.zih.tu-dresden.de/docs/software/tensorboard.md
+++ b/doc.zih.tu-dresden.de/docs/software/tensorboard.md
@@ -6,13 +6,15 @@ application.
 
 ## Using JupyterHub
 
-The easiest way to use TensorBoard is via [JupyterHub](../access/jupyterhub.md). The default
-TensorBoard log directory is set to `/tmp/<username>/tf-logs` on the compute node, where Jupyter
-session is running. In order to show your own directory with logs, it can be soft-linked to the
-default folder. Open a "New Launcher" menu (`Ctrl+Shift+L`) and select "Terminal" session. It
-will start new terminal on the respective compute node. Create a directory `/tmp/$USER/tf-logs`
-and link it with your log directory
-`ln -s <your-tensorboard-target-directory> <local-tf-logs-directory>`
+The easiest way to use TensorBoard is via [JupyterHub](../access/jupyterhub.md). By default,
+TensorBoard is configured to read log data from `/tmp/<username>/tf-logs` on the compute node on
+which the Jupyter session is running. In order to show your own log data from a different directory,
+soft-link this directory with `/tmp/<username>/tf-logs` in order to make TensorBoard reading your
+log data. Note, that the directory `/tmp/<username>/tf-logs` might not exist and you have to
+create it first. Therefore, open a "New Launcher" (`Ctrl+Shift+L`) and select "Terminal" session.
+It will start a new terminal on the respective compute node. Then you can create the directory
+`/tmp/<username>/tf-logs` and link it with the directory where your own log data is located.
+Consider the following commands to do so:
 
 ```Bash
 mkdir -p /tmp/$USER/tf-logs