diff --git a/doc/basics.md b/doc/basics.md
index 1b7bdbe6825c07f13b184efc79b9f8694c048fd2..eda06f92285b3d5e1055390e04526152121ab8ce 100644
--- a/doc/basics.md
+++ b/doc/basics.md
@@ -119,11 +119,6 @@ Let $`x^{(1)},\dots,x^{(N)}\sim\pi`$ be independent (random) samples and assume
 
 The empirical regression problem then reads
 
-```math
-\text{Find}\qquad \Psi_\vartheta
-= \operatorname*{arg\, min}_{\Psi_\theta\in\mathcal{M}_{d,\varphi}} \frac{1}{N} \sum_{i=1}^N \bigl(f^{(i)} - \Psi_\theta(x^{(i)})\bigr)^2
-=: \operatorname*{arg\, min}_{\Psi_\theta\in\mathcal{M}_{d,\varphi}} \mathcal{L}_N(\Psi_\theta)
-```
 
 > **Definition** (loss function):
 > A _loss functions_ is any function, which measures how good a neural network approximates the target values.