From 40201c4604a5e360adc86fd9e34c21c66a5aef2c Mon Sep 17 00:00:00 2001
From: udlbook <110402648+udlbook@users.noreply.github.com>
Date: Tue, 25 Jul 2023 08:53:52 -0400
Subject: [PATCH] Created using Colaboratory
---
Notebooks/Chap03/3_1_Shallow_Networks_I.ipynb | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/Notebooks/Chap03/3_1_Shallow_Networks_I.ipynb b/Notebooks/Chap03/3_1_Shallow_Networks_I.ipynb
index 0f6f5c2..2a0c235 100644
--- a/Notebooks/Chap03/3_1_Shallow_Networks_I.ipynb
+++ b/Notebooks/Chap03/3_1_Shallow_Networks_I.ipynb
@@ -4,7 +4,7 @@
"metadata": {
"colab": {
"provenance": [],
- "authorship_tag": "ABX9TyNagjz+fy8uCFG71RAVMUVT",
+ "authorship_tag": "ABX9TyNO9SPfZa/RV0mp9XWuD3s5",
"include_colab_link": true
},
"kernelspec": {
@@ -31,7 +31,7 @@
"source": [
"# **Notebook 3.1 -- Shallow neural networks I**\n",
"\n",
- "The purpose of this practical is to gain some familiarity with shallow neural networks. It works through the example similar to figure 3.3 and experiments with different activation functions.
\n",
+ "The purpose of this notebook is to gain some familiarity with shallow neural networks. It works through an example similar to figure 3.3 and experiments with different activation functions.
\n",
"\n",
"Work through the cells below, running each cell in turn. In various places you will see the words \"TO DO\". Follow the instructions at these places and write code to complete the functions. There are also questions interspersed in the text.\n",
"\n",
@@ -58,7 +58,7 @@
{
"cell_type": "markdown",
"source": [
- "Let's first construct the shallow neural network with one input, three hidden units, and one output described in section 4.1 of the book."
+ "Let's first construct the shallow neural network with one input, three hidden units, and one output described in section 3.1 of the book."
],
"metadata": {
"id": "wQDy9UzXpnf5"