diff --git a/ch03/01_main-chapter-code/ch03.ipynb b/ch03/01_main-chapter-code/ch03.ipynb
index d5cb1ec..1ba30a9 100644
--- a/ch03/01_main-chapter-code/ch03.ipynb
+++ b/ch03/01_main-chapter-code/ch03.ipynb
@@ -271,7 +271,7 @@
    "id": "299baef3-b1a8-49ba-bad4-f62c8a416d83",
    "metadata": {},
    "source": [
-    "- (In this book, we follow the common machine learning and deep learning convention where training examples are represented as rows and feature values as columns; in the caase of the tensor shown above, each row represents a word, and each column represents an embedding dimension)\n",
+    "- (In this book, we follow the common machine learning and deep learning convention where training examples are represented as rows and feature values as columns; in the case of the tensor shown above, each row represents a word, and each column represents an embedding dimension)\n",
     "\n",
     "- The primary objective of this section is to demonstrate how the context vector $z^{(2)}$\n",
     "  is calculated using the second input sequence, $x^{(2)}$, as a query\n",