diff --git a/beginner_source/examples_autograd/polynomial_autograd.py b/beginner_source/examples_autograd/polynomial_autograd.py
index 65ab5892d9e..05744ff560c 100755
--- a/beginner_source/examples_autograd/polynomial_autograd.py
+++ b/beginner_source/examples_autograd/polynomial_autograd.py
@@ -4,7 +4,7 @@
 -------------------------------
 
 A third order polynomial, trained to predict :math:`y=\sin(x)` from :math:`-\pi`
-to :math:`pi` by minimizing squared Euclidean distance.
+to :math:`\pi` by minimizing squared Euclidean distance.
 
 This implementation computes the forward pass using operations on PyTorch
 Tensors, and uses PyTorch autograd to compute gradients.
diff --git a/beginner_source/examples_autograd/polynomial_custom_function.py b/beginner_source/examples_autograd/polynomial_custom_function.py
index 33fc1a24688..4a0ea4fc9d8 100755
--- a/beginner_source/examples_autograd/polynomial_custom_function.py
+++ b/beginner_source/examples_autograd/polynomial_custom_function.py
@@ -1,10 +1,10 @@
 # -*- coding: utf-8 -*-
-"""
+r"""
 PyTorch: Defining New autograd Functions
 ----------------------------------------
 
 A third order polynomial, trained to predict :math:`y=\sin(x)` from :math:`-\pi`
-to :math:`pi` by minimizing squared Euclidean distance. Instead of writing the
+to :math:`\pi` by minimizing squared Euclidean distance. Instead of writing the
 polynomial as :math:`y=a+bx+cx^2+dx^3`, we write the polynomial as
 :math:`y=a+b P_3(c+dx)` where :math:`P_3(x)=\frac{1}{2}\left(5x^3-3x\right)` is
 the `Legendre polynomial`_ of degree three.