Explaining regression loss function for data frame analytics jobs #331

This PR adds a notebook explains the properties of different loss functions available for the machine learning data frame analytics regression jobs and give pointers on when to choose which loss function.

It intends to be linked in the "Concepts" section of the documentation and provide users with more insights than it is possible in the scope of "Concepts".

Author: valeriy42

Machine Learning/Regression Loss Functions/README.md

@@ -0,0 +1,32 @@
+# Regression Loss Functions
+
+This notebook explains the properties of different loss functions available for the
+machine learning data frame analytics regression jobs and give pointers on when to
+choose which loss function.
+
+Set up a local instance of Jupyter using the following instructions
+
+1. Set up a virtual environment called `env` 
+
+```
+python3 -m venv env
+``` 
+
+2. Activate it
+
+```
+source env/bin/activate
+```
+
+3. Install the required dependencies for your chosen Jupyter notebook
+
+```
+pip install -r requirements.txt
+```
+
+4. Launch Jupyter
+
+```
+jupyter notebook
+```
+