fix

docs/personalization/recommendation_models.md

@@ -217,7 +217,7 @@ The logic used for resolving a submodel is as follows:
 ### Dynamic attributes
 
 Dynamic attribute submodels eliminate the need for manual grouping and simplify configuration.
-They allow for simpler, faster, and less demanding recommendation tests using different attributes, because all you need to do is make one request and rebuild the model.
+They allow for simpler, faster, and less demanding recommendation models building using different attributes, because all you need to do is make one request and rebuild the model.
 
 They work best in straightforward cases when you filter by the value of the attribute.
 
@@ -226,7 +226,7 @@ Dynamic attribute submodels:
 - operate only on [nominal attributes](recommendation_models#nominal-attributes) (numeric attributes are not supported)
 - can be used for [popularity](recommendation_models#popularity-models) and [collaborative](recommendation_models#collaborative-models) types of models (as they support submodels)
 - have limitation of max. 50 attribute values (if more, you need to follow standard procedure - manual configuration by [[= product_name_base =]] Team)
-- operate on scenarios thay use submodel support for model (`Submodels` data type)
+- operate on scenarios with the selected `Submodels` data type option
 - require sending a request and building a model
 - are calculated for all new attribute values after import
 - are always up-to-date with the imported items