Update 11_targeting_variants_for_maximum_impact.md

Signed-off-by: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com>

Author: AlxdrPolyakov

_case_studies/11_targeting_variants_for_maximum_impact.md

@@ -4,7 +4,7 @@ layout: page
 description: >-
   This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric.
 summary: >-
-  This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of   the ERUPT metric. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. 
+  This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. 
 image: assets/causaltune-targeting.png
 image-alt: Targeting variants for maximum impact
 link: https://medium.com/@alexander.polyakov/targeting-variants-for-maximum-impact-bdf26213d7bc