Nb 1

recipes/quickstart/Multi-Modal-RAG/README.md

@@ -8,7 +8,7 @@
 
 ## Resources used: 
 
-Credit and Thanks to List of models and libraries used in the showcase:
+Credit and Thanks to List of models and resources used in the showcase:
 
 Firstly, thanks to the author here for providing this dataset on which we base our excercise []()
 

recipes/quickstart/Multi-Modal-RAG/notebooks/Part_1_Data_Preperation.ipynb

@@ -5,7 +5,11 @@
    "id": "01af3b74-b3b9-4c1f-b41d-2911e7f19ffe",
    "metadata": {},
    "source": [
-    "## Data Preperation Notebook"
+    "## Data Preperation Notebook\n",
+    "\n",
+    "To make the experience consistent, we will use [this link]() for getting access to our dataset. To credit, thanks to the author [here]() for making it available. \n",
+    "\n",
+    "The author of this series empathises with all Kagglers aspiring to be Grandmasters: Please upvote the dataset version on Kaggle if you enjoy this course."
    ]
   },
   {
@@ -21,7 +25,13 @@
    "id": "addccd91-3c83-45bd-83b0-d5147fdc40ff",
    "metadata": {},
    "source": [
-    "### Removing Corrupt Images"
+    "### Removing Corrupt Images\n",
+    "\n",
+    "Like everything in the real world, all datasets come with some corruption. Thankfully here we can fix it ourselves. \n",
+    "\n",
+    "Obviously this is a great first step to check. Unfortunately, the author of the notebook realised there are corrupt images after crashing a GPU script 8 hours later. \n",
+    "\n",
+    "We can now use this hindsight to act like smart data scientists and fix this first. "
    ]
   },
   {
@@ -29,7 +39,11 @@
    "id": "ee016cfd-5255-4809-96ec-406ee6947e24",
    "metadata": {},
    "source": [
-    "#### Variables and Paths"
+    "#### Variables and Paths\n",
+    "\n",
+    "Let's first download the dataset and set our variables to point to it. \n",
+    "\n",
+    "Remember, this is something you will change, don't rush the shift+enter fingers yet! It will come soon!"
    ]
   },
   {