diff --git a/examples/face_recognition_knn.py b/examples/face_recognition_knn.py
index d99b760b55acc673eb1b6baa9a6b6c55dfeb2cdc..b16c46d9d662058c1ee09c78ad7a9a69782f4d93 100644
--- a/examples/face_recognition_knn.py
+++ b/examples/face_recognition_knn.py
@@ -7,7 +7,7 @@ and make a prediction for an unknown person in a feasible computation time.
 
 Algorithm Description:
 The knn classifier is first trained on a set of labeled (known) faces and can then predict the person
-in an unknown image by finding the k most similar faces (images with closet face-features under eucledian distance)
+in an unknown image by finding the k most similar faces (images with closet face-features under euclidean distance)
 in its training set, and performing a majority vote (possibly weighted) on their label.
 
 For example, if k=3, and the three closest face images to the given image in the training set are one image of Biden
diff --git a/examples/facerec_ipcamera_knn.py b/examples/facerec_ipcamera_knn.py
index 352efdbcd27465f63f7f427cdaa500d42c36e6d6..ae92234164b297e7e771eaaece55ae780b8b63dd 100644
--- a/examples/facerec_ipcamera_knn.py
+++ b/examples/facerec_ipcamera_knn.py
@@ -7,7 +7,7 @@ and make a prediction for an unknown person in a feasible computation time.
 
 Algorithm Description:
 The knn classifier is first trained on a set of labeled (known) faces and can then predict the person
-in a live stream by finding the k most similar faces (images with closet face-features under eucledian distance)
+in a live stream by finding the k most similar faces (images with closet face-features under euclidean distance)
 in its training set, and performing a majority vote (possibly weighted) on their label.
 
 For example, if k=3, and the three closest face images to the given image in the training set are one image of Biden