From 1be74b43233d6ff27053cd75eb650a22badde14f Mon Sep 17 00:00:00 2001
From: Giovanni Volpe <46021832+giovannivolpe@users.noreply.github.com>
Date: Mon, 15 Apr 2024 20:56:01 +0200
Subject: [PATCH] u

---
 tutorials/getting-started/GS111_first_model.ipynb | 6 +++---
 tutorials/getting-started/GS121_configure.ipynb   | 2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/tutorials/getting-started/GS111_first_model.ipynb b/tutorials/getting-started/GS111_first_model.ipynb
index 3702977b..09d22679 100644
--- a/tutorials/getting-started/GS111_first_model.ipynb
+++ b/tutorials/getting-started/GS111_first_model.ipynb
@@ -4,16 +4,16 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Training your first model\n",
+    "# Training Your First Model\n",
     "\n",
-    "In this section, you'll train a simple feedforward neural network on MNIST using Deeplay. You'll define the model, loss function, optimizer, and training loop, and then train the model on the dataset."
+    "In this section, you'll train a simple feedforward neural network on the MNIST using Deeplay. You'll define the model, loss function, optimizer, and training loop, and then train the model on the dataset."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Loading the dataset\n",
+    "## Loading the Dataset\n",
     "\n",
     "Data can come from anywhere. MNIST is most easily loaded using the torchvision library, which provides a simple interface for downloading and loading common datasets. Here, you'll load the MNIST dataset and create a PyTorch DataLoader to iterate over the dataset in batches."
    ]
diff --git a/tutorials/getting-started/GS121_configure.ipynb b/tutorials/getting-started/GS121_configure.ipynb
index 931b298e..fe157d01 100644
--- a/tutorials/getting-started/GS121_configure.ipynb
+++ b/tutorials/getting-started/GS121_configure.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Working with Deeplay Modules\n",
+    "# Configuring Deeplay Objects\n",
     "\n",
     "In this section, you'll explore the difference between Deeplay and PyTorch modules. You'll learn how to create and build Deeplay modules as well as how to configure their properties."
    ]