Update Intro_to_CV.ipynb

bolded some sections in 1.1

Author: Wei-Ji-Chen

2023/SP23/intro-cv-series/workshop-1/Intro_to_CV.ipynb

@@ -42,7 +42,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "What is Computer Vision? \n",
+        "### What is Computer Vision?\n",
         "\n",
         "Computer Vision is a subfield of AI that focuses on computers deriving and understanding information based on visual data - images, videos, etc. The applications are numerous including but not limited to autonomous vehicles, facial recognition, and medical imaging. "
       ]
@@ -52,7 +52,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "Terminology \n",
+        "### Terminology\n",
         "\n",
         "Before diving into Computer Vision, we have to understand the terminology relevant to AI. Often times, we hear these words being tossed around, and even used interchangeably: Artificial Intellignece, Machine Learning, Deep Learning, Neural Networks, etc. What do they mean and what's their relationship with each other? \n",
         "\n",
@@ -72,6 +72,8 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
+        "### General Machine Learning\n",
+        "\n",
         "Now that we're clear o the terminology, let's talk about the default method to mimic human intelligence, Machine Learning. In doing so, you will see why neural networks and deep learning exist - and their necessity in Computer Vision. We'll be using the MNIST dataset to demostrate ML. "
       ]
     },