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cog-imperial · Aug 13, 2023 · dbffa25 · dbffa25
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diff --git a/docs/index.rst b/docs/index.rst
@@ -17,6 +17,7 @@ This small example illustrates how to use ENTMOOT.
     import random
 
     # This is the function you want to minimize.
+    # In most use cases this will be something terribly complicated like a simulation or a real-world experiment
     def my_func(x: float) -> float:
         # randomly disturbed function f(x) = x^2 + 1 + eps
         return x**2 + 1 + random.uniform(-0.2, 0.2)

diff --git a/docs/installation.rst b/docs/installation.rst
@@ -30,7 +30,7 @@ Gurobi or Pyomo?
 -----------------
 You can work with ENTMOOT using Gurobi or Pyomo.
 
-* `Gurobi <https://www.gurobi.com/>`__ is a commercial mathematical optimization solver and very fast. Not only
+* `Gurobi <https://www.gurobi.com/>`__ is a commercial mathematical optimization solver which is very fast. Not only
   in solving the corresponding optimization problem but also in building it. Using Gurobi requires a valid license. Note
   that Gurobi offers `free academic licenses <https://www.gurobi.com/academia/academic-program-and-licenses/>`__.
 * `Pyomo <http://www.pyomo.org/>`__ is an open-source optimization modeling language with APIs to several commercial and