diff --git a/ch03/01_main-chapter-code/ch03.ipynb b/ch03/01_main-chapter-code/ch03.ipynb
index eb68a77..d5cb1ec 100644
--- a/ch03/01_main-chapter-code/ch03.ipynb
+++ b/ch03/01_main-chapter-code/ch03.ipynb
@@ -205,7 +205,10 @@
    "id": "fcc7c7a2-b6ab-478f-ae37-faa8eaa8049a",
    "metadata": {},
    "source": [
-    "<img src=\"https://sebastianraschka.com/images/LLMs-from-scratch-images/ch03_compressed/07.webp\" width=\"400px\">"
+    "<img src=\"https://sebastianraschka.com/images/LLMs-from-scratch-images/ch03_compressed/07.webp\" width=\"400px\">\n",
+    "\n",
+    "- (Please note that the numbers in this figure are truncated to one\n",
+    "digit after the decimal point to reduce visual clutter; similarly, other figures may also contain truncated values)"
    ]
   },
   {
@@ -268,11 +271,13 @@
    "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",
+    "\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",
     "\n",
     "- The figure depicts the initial step in this process, which involves calculating the attention scores ω between $x^{(2)}$\n",
-    "  and all other input elements through a dot product operation."
+    "  and all other input elements through a dot product operation"
    ]
   },
   {
@@ -517,7 +522,10 @@
    "id": "11c0fb55-394f-42f4-ba07-d01ae5c98ab4",
    "metadata": {},
    "source": [
-    "<img src=\"https://sebastianraschka.com/images/LLMs-from-scratch-images/ch03_compressed/11.webp\" width=\"400px\">"
+    "<img src=\"https://sebastianraschka.com/images/LLMs-from-scratch-images/ch03_compressed/11.webp\" width=\"400px\">\n",
+    "\n",
+    "- (Please note that the numbers in this figure are truncated to two\n",
+    "digits after the decimal point to reduce visual clutter; the values in each row should add up to 1.0 or 100%; similarly, digits in other figures are truncated)"
    ]
   },
   {
@@ -2019,7 +2027,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,