Merge pull request #79 from hi-anji/main

Update 01_introduction.ipynb

AA2324/course/01_introduction/01_introduction.ipynb

@@ -398,13 +398,13 @@
     }
    },
    "source": [
-    "##  🎯Course Objective\n",
+    "##  🎯Course Objectives\n",
     "\n",
     "- Introducing you to the basic principles of **Machine Learning**\n",
     "- Knowledge on the **main learning modalities** (supervised, unsupervised, parametric/non parametric)\n",
     "- Knowledge on the **main ML algorithm strengths and weaknesses** (no free lunch theorem)\n",
     "- Develop awareness of the **mathematical tools** behind.\n",
-    "- Setting **strong foundations** for more advances courses (i.e. Deep Learning)\n",
+    "- Setting **strong foundations** for more advanced courses (i.e. Deep Learning)\n",
     "- Develop **critical thinking**/raise next generation of **scientists**\n",
     "- Show a few **cool, practical applications**"
    ]
@@ -437,7 +437,7 @@
     }
    },
    "source": [
-    "# 👩🏾‍💻Technology is power (toolset to use)\n",
+    "# 👩🏾‍💻Technology is power (toolsets to use)\n",
     "\n",
     "### Toolsets: \n",
     "* Python (widely used in ML)\n",
@@ -607,10 +607,10 @@
     "## AI Job Landscape - An example\n",
     "\n",
     "\n",
-    "An AI&ML student from previous year given that he/she studied hard AI&ML (along with Unit I and AI Lab) was able to **secure an internship with Hewlett-Packard Enterprise (HPE)**. The student told me that:\n",
-    "- she/he was selected among 40 candidates (1:40)\n",
-    "- she/he  was preferred to graduated students (students obtained the master)\n",
-    "- she/he will work with international team\n",
+    "An AI&ML student from previous year, given that they studied hard AI&ML (along with Unit I and AI Lab), was able to **secure an internship with Hewlett-Packard Enterprise (HPE)**. The student told me that:\n",
+    "- they were selected among 40 candidates (1:40)\n",
+    "- they were preferred to graduated students (students obtained the master)\n",
+    "- they will work with international team\n",
     "\n",
     "<div align='center'><img src='https://upload.wikimedia.org/wikipedia/commons/thumb/a/ad/HP_logo_2012.svg/120px-HP_logo_2012.svg.png'></div>"
    ]
@@ -754,14 +754,14 @@
    "source": [
     "# What is ML (Informal)\n",
     "\n",
-    "First definition in 1959 by Arthur Lee Samuel\n",
+    "First definition in 1959 by Arthur Lee Samuel:\n",
     "\n",
     ">ML is the field of study that gives computers the\n",
     "ability to learn without being explicitly programmed. \n",
     "\n",
     "* Common definition (by Tom Mitchell):\n",
     "\n",
-    "> ML is the study of computer algorithms that improve automatically through experience\n"
+    "> ML is the study of computer algorithms that improve automatically through experience.\n"
    ]
   },
   {
@@ -794,7 +794,7 @@
     "\n",
     "<img src=\"figs/07_ai_beyond.png\" width='40%'/>\n",
     "\n",
-    "- Computer Vision, Robotics, NLP in some sense they are all applications of AI to a domain.\n",
+    "- Computer Vision, Robotics, NLP are all, in some sense, applications of AI to a domain.\n",
     "- `vision = let machine see the world`\n",
     "\n",
     "<small><sup>Graphics from [ballan2019_introML]</sup></small>"
@@ -873,7 +873,7 @@
     }
    },
    "source": [
-    "### To solve problems, but which kind of problems?\n",
+    "### To solve problems, but what kind of problems?\n",
     "\n",
     "There are two types of problems."
    ]
@@ -935,7 +935,7 @@
    },
    "source": [
     "### Why not to use a traditional algorithmic approach?\n",
-    "- Impossible to exactly formalize the problem (and so to give an algorithmic solution)\n",
+    "- Impossibility to exactly formalize the problem (and so to give an algorithmic solution)\n",
     "- Presence of noise, uncertainty, too many variations in the data\n",
     "- High complexity in formulating a solution, i.e. it cannot be done manually\n",
     "- Lack of compiled knowledge with respect to the problem to be solved"
@@ -997,7 +997,7 @@
     "- No one trained humans (maybe \"God\"/evolution/X did...)\n",
     "- Can you recognize this face?\n",
     " - **...but let's do it like the computer does it**\n",
-    " - **right I forgot to zoom in**"
+    " - **right, I forgot to zoom in**"
    ]
   },
   {
@@ -1117,7 +1117,7 @@
    "source": [
     "## Applications\n",
     "\n",
-    "1. **Classification:** Determine which discrete category the example is\n",
+    "1. **Classification:** Determine which discrete category the example belongs to\n",
     "2. **Recognizing patterns:** Speech Recognition, Facial identity, etc\n",
     "3. **Recommender Systems:** Noisy data, commercial pay-off (e.g., Amazon, Netflix).\n",
     "4. **Information retrieval:** Find documents or images with similar content\n",