diff --git a/docs/src/LinearSurrogate.md b/docs/src/LinearSurrogate.md
index 0d9c5c5a..2acff979 100644
--- a/docs/src/LinearSurrogate.md
+++ b/docs/src/LinearSurrogate.md
@@ -1,7 +1,7 @@
 ## Linear Surrogate
 Linear Surrogate is a linear approach to modeling the relationship between a scalar response or dependent variable and one or more explanatory variables. We will use Linear Surrogate to optimize following function:
 
-$f(x) = sin(x) + log(x)$.
+$f(x) = \sin(x) + \log(x)$
 
 First of all we have to import these two packages: `Surrogates` and `Plots`.
 
diff --git a/docs/src/radials.md b/docs/src/radials.md
index 4fbe50d6..2ed4a98b 100644
--- a/docs/src/radials.md
+++ b/docs/src/radials.md
@@ -1,7 +1,9 @@
 ## Radial Surrogates
 The Radial Basis Surrogate model represents the interpolating function as a linear combination of basis functions, one for each training point. Let's start with something easy to get our hands dirty. I want to build a surrogate for:
 
-`f(x) = log(x)*x^2+x^3``
+```math
+f(x) = \log(x) \cdot x^2+x^3
+```
 
 Let's choose the Radial Basis Surrogate for 1D. First of all we have to import these two packages: `Surrogates` and `Plots`,