diff --git a/tensorflow/python/ops/math_ops.py b/tensorflow/python/ops/math_ops.py
index 0ca39af2ed2379..72d62c973239f6 100644
--- a/tensorflow/python/ops/math_ops.py
+++ b/tensorflow/python/ops/math_ops.py
@@ -4229,6 +4229,23 @@ def polyval(coeffs, x, name=None):
      p(x) = coeffs[n-1] + x * (coeffs[n-2] + ... + x * (coeffs[1] +
             x * coeffs[0]))
 
+  Usage Example:
+
+  >>> tf.math.polyval([2, 1, 0], 3) # evaluates 2 * (3**2) + 1 * (3**1) + 0 * (3**0)
+  <tf.Tensor: shape=(), dtype=int32, numpy=21>
+
+  `tf.math.polyval` can also be used in polynomial regression. Taking
+  advantage of this function can facilitate writing a polynomial equation
+  as compared to explicitly writing it out, especially for higher degree
+  polynomials.
+
+  >>> x = tf.constant(3)
+  >>> theta1 = tf.Variable(2)
+  >>> theta2 = tf.Variable(1)
+  >>> theta3 = tf.Variable(0)
+  >>> tf.math.polyval([theta1, theta2, theta3], x)
+  <tf.Tensor: shape=(), dtype=int32, numpy=21>
+
   Args:
     coeffs: A list of `Tensor` representing the coefficients of the polynomial.
     x: A `Tensor` representing the variable of the polynomial.