lectures/01_intro.ipynb

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    "![](img/330-banner.png)"
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   "source": [
    "# Lecture 1: Course Introduction \n",
    "\n",
    "UBC 2022 Summer\n",
    "\n",
    "Instructor: Mehrdad Oveisi"
   ]
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   "source": [
    "Course webpage: \n",
    "\n",
    "> https://github.com/UBC-CS/cpsc330-2022s\n"
   ]
  },
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    "tags": []
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   "source": [
    "### Meet Eva (a fictitious persona)!\n",
    "\n",
    "![](img/eva-hi.png)\n",
    "\n",
    "Eva is among one of you. She has some experience in Python programming. She knows machine learning as a buzz word. During her recent internship, she has developed some interest and curiosity in the field. She wants to learn what is it and how to use it. She is a curious person and usually has a lot of questions!  "
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   "source": [
    "## Imports"
   ]
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   "source": [
    "import glob\n",
    "import os\n",
    "import re\n",
    "import sys\n",
    "from collections import Counter, defaultdict\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "sys.path.append(\"code/.\")\n",
    "import graphviz\n",
    "import IPython\n",
    "import mglearn\n",
    "from IPython.display import HTML, display\n",
    "from plotting_functions import *\n",
    "from sklearn.dummy import DummyClassifier\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.linear_model import LinearRegression, LogisticRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.pipeline import Pipeline, make_pipeline\n",
    "from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor, export_graphviz\n",
    "from utils import *\n",
    "\n",
    "plt.rcParams[\"font.size\"] = 16\n",
    "pd.set_option(\"display.max_colwidth\", 200)"
   ]
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   "source": [
    "## Learning outcomes \n",
    "From this lecture, you will be able to \n",
    "\n",
    "- explain the motivation to study machine learning;\n",
    "- explain supervised machine learning; \n",
    "- navigate through the course material;\n",
    "- be familiar with the policies and how the class is going to run; \n",
    "- set up your computer for the course. "
   ]
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   "source": [
    "<br><br>"
   ]
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   },
   "source": [
    "## Why machine learning (ML)? [[video](https://www.youtube.com/watch?v=-1hTcS5ZE4w&t=1s)]"
   ]
  },
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   "source": [
    "Check out [the accompanying video](https://www.youtube.com/watch?v=-1hTcS5ZE4w&t=1s) on this material."
   ]
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   "source": [
    "### Prevalence of ML\n",
    "\n",
    "Let's look at some examples. \n",
    "\n",
    "<!-- <img src=\"img/ml-examples.png\" height=\"1000\" width=\"1000\">  -->\n",
    "![](img/ml-examples.png)\n"
   ]
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   "source": [
    "- Image sources \n",
    "    - [Voice assistants](https://geeksfl.com/blog/best-voice-assistant/)\n",
    "    - [Google News](https://news.google.com)    \n",
    "    - [Recommendation systems](https://en.wikipedia.org/wiki/Recommender_system)\n",
    "    - [Face Recognition source](https://startupleague.online/blog/3dss-tech-facial-recognition-technology/)\n",
    "    - [Auto-completion](https://9to5google.com/2020/08/10/android-11-autofill-keyboard/)\n",
    "    - [Stock market prediction](https://hbr.org/2019/12/what-machine-learning-will-mean-for-asset-managers)    \n",
    "    - [Character recognition](https://en.wikipedia.org/wiki/Handwriting_recognition)    \n",
    "    - [AlphaGo](https://deepmind.com/alphago-china)\n",
    "    - [Self-driving cars](https://mc.ai/artificial-intelligence-in-self-driving-cars%E2%80%8A-%E2%80%8Ahow-far-have-we-gotten/)\n",
    "    - [Drug discovery](https://www.nature.com/articles/d41586-018-05267-x)\n",
    "    - [Cancer detection](https://venturebeat.com/2018/10/12/google-ai-claims-99-accuracy-in-metastatic-breast-cancer-detection/)"
   ]
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   "source": [
    "### Saving time and scaling products \n",
    "\n",
    "- Imagine writing a program for **spam** identification, i.e., whether an email is spam or non-spam. \n",
    "- Traditional programming \n",
    "    - Come up with **rules** using human understanding of spam messages. \n",
    "    - Time consuming and hard to come up with robust set of rules. \n",
    "- Machine learning\n",
    "    - Collect large amount of **data** of spam and non-spam emails and let the machine learning algorithm figure out rules. \n",
    "- With machine learning, you're likely to \n",
    "    - Save time \n",
    "    - Customize and scale products "
   ]
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   "source": [
    "<br><br>"
   ]
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   "source": [
    "## Supervised machine learning "
   ]
  },
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    "### Types of machine learning\n",
    "\n",
    "Here are some typical learning problems. \n",
    "\n",
    "- **Supervised learning** ([Gmail spam filtering](https://support.google.com/a/answer/2368132?hl=en))\n",
    "    - Training a model from input data and its corresponding targets to predict targets for new examples.     \n",
    "- Unsupervised learning ([Google News](https://news.google.com/))\n",
    "    - Training a model to find patterns in a dataset, typically an unlabeled dataset.\n",
    "- Reinforcement learning ([AlphaGo](https://deepmind.com/research/case-studies/alphago-the-story-so-far))\n",
    "    - A family of algorithms for finding suitable actions to take in a given situation in order to maximize a reward. \n",
    "- Recommendation systems ([Amazon item recommendation system](https://www.cs.umd.edu/~samir/498/Amazon-Recommendations.pdf))\n",
    "    - Predict the \"rating\" or \"preference\" a user would give to an item.    "
   ]
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   "source": [
    "### What is supervised machine learning (ML)? \n",
    "\n",
    "- Training data comprises a set of observations ($X$) and their corresponding targets ($y$). \n",
    "- We wish to find a model function $f$ that relates $X$ to $y$.\n",
    "- We use the model function to predict targets of new examples. \n",
    "\n",
    "![](img/sup-learning.png)\n",
    "<!-- <img src=\"img/sup-learning.png\" height=\"800\" width=\"800\">  -->\n"
   ]
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   "source": [
    "### Example: Predict whether a message is spam or not "
   ]
  },
  {
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   "metadata": {},
   "source": [
    "#### Input features $X$ and target $y$"
   ]
  },
  {
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   "id": "9e13ac7b-ebcb-4d39-b869-7b8131f087fb",
   "metadata": {},
   "source": [
    "Do not worry about the code and syntax for now. \n"
   ]
  },
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   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "Download SMS Spam Collection Dataset from [here](https://www.kaggle.com/uciml/sms-spam-collection-dataset)."
   ]
  },
  {
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   "execution_count": 3,
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     "hide-input"
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       "#T_a7508_row0_col0, #T_a7508_row0_col1, #T_a7508_row1_col0, #T_a7508_row1_col1, #T_a7508_row2_col0, #T_a7508_row2_col1, #T_a7508_row3_col0, #T_a7508_row3_col1, #T_a7508_row4_col0, #T_a7508_row4_col1 {\n",
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       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_a7508_level0_col0\" class=\"col_heading level0 col0\" >target</th>\n",
       "      <th id=\"T_a7508_level0_col1\" class=\"col_heading level0 col1\" >sms</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_a7508_level0_row0\" class=\"row_heading level0 row0\" >3130</th>\n",
       "      <td id=\"T_a7508_row0_col0\" class=\"data row0 col0\" >spam</td>\n",
       "      <td id=\"T_a7508_row0_col1\" class=\"data row0 col1\" >LookAtMe!: Thanks for your purchase of a video clip from LookAtMe!, you've been charged 35p. Think you can do better? Why not send a video in a MMSto 32323.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_a7508_level0_row1\" class=\"row_heading level0 row1\" >106</th>\n",
       "      <td id=\"T_a7508_row1_col0\" class=\"data row1 col0\" >ham</td>\n",
       "      <td id=\"T_a7508_row1_col1\" class=\"data row1 col1\" >Aight, I'll hit you up when I get some cash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_a7508_level0_row2\" class=\"row_heading level0 row2\" >4697</th>\n",
       "      <td id=\"T_a7508_row2_col0\" class=\"data row2 col0\" >ham</td>\n",
       "      <td id=\"T_a7508_row2_col1\" class=\"data row2 col1\" >Don no da:)whats you plan?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_a7508_level0_row3\" class=\"row_heading level0 row3\" >856</th>\n",
       "      <td id=\"T_a7508_row3_col0\" class=\"data row3 col0\" >ham</td>\n",
       "      <td id=\"T_a7508_row3_col1\" class=\"data row3 col1\" >Going to take your babe out ?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_a7508_level0_row4\" class=\"row_heading level0 row4\" >3454</th>\n",
       "      <td id=\"T_a7508_row4_col0\" class=\"data row4 col0\" >ham</td>\n",
       "      <td id=\"T_a7508_row4_col1\" class=\"data row4 col1\" >No need lar. Jus testing e phone card. Dunno network not gd i thk. Me waiting 4 my sis 2 finish bathing so i can bathe. Dun disturb u liao u cleaning ur room.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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   "source": [
    "sms_df = pd.read_csv(\"data/spam.csv\", encoding=\"latin-1\")\n",
    "sms_df = sms_df.drop(columns = [\"Unnamed: 2\", \"Unnamed: 3\", \"Unnamed: 4\"])\n",
    "sms_df = sms_df.rename(columns={\"v1\": \"target\", \"v2\": \"sms\"})\n",
    "train_df, test_df = train_test_split(sms_df, test_size=0.10, random_state=42)\n",
    "train_df.head().style.set_properties(**{\"text-align\": \"left\"})"
   ]
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   "metadata": {
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   },
   "source": [
    "#### Training a supervised machine learning model with $X$ and $y$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6f38510c-ad87-4d48-b267-cfe7bf44aa83",
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   "source": [
    "X_train, y_train = train_df[\"sms\"], train_df[\"target\"]\n",
    "X_test, y_test = test_df[\"sms\"], test_df[\"target\"]\n",
    "\n",
    "clf = Pipeline(\n",
    "    [\n",
    "        (\"vect\", CountVectorizer(max_features=5000)),\n",
    "        (\"clf\", LogisticRegression(max_iter=5000)),\n",
    "    ]\n",
    ")\n",
    "clf.fit(X_train, y_train);"
   ]
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   },
   "source": [
    "#### Predicting on unseen data using the trained model"
   ]
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       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_139b6_level0_col0\" class=\"col_heading level0 col0\" >sms</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_139b6_level0_row0\" class=\"row_heading level0 row0\" >3245</th>\n",
       "      <td id=\"T_139b6_row0_col0\" class=\"data row0 col0\" >Funny fact Nobody teaches volcanoes 2 erupt, tsunamis 2 arise, hurricanes 2 sway aroundn no 1 teaches hw 2 choose a wife Natural disasters just happens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_139b6_level0_row1\" class=\"row_heading level0 row1\" >944</th>\n",
       "      <td id=\"T_139b6_row1_col0\" class=\"data row1 col0\" >I sent my scores to sophas and i had to do secondary application for a few schools. I think if you are thinking of applying, do a research on cost also. Contact joke ogunrinde, her school is one me the less expensive ones</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_139b6_level0_row2\" class=\"row_heading level0 row2\" >1044</th>\n",
       "      <td id=\"T_139b6_row2_col0\" class=\"data row2 col0\" >We know someone who you know that fancies you. Call 09058097218 to find out who. POBox 6, LS15HB 150p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_139b6_level0_row3\" class=\"row_heading level0 row3\" >2484</th>\n",
       "      <td id=\"T_139b6_row3_col0\" class=\"data row3 col0\" >Only if you promise your getting out as SOON as you can. And you'll text me in the morning to let me know you made it in ok.</td>\n",
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       "  </tbody>\n",
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    "pd.DataFrame(X_test[0:4]).style.set_properties(**{\"text-align\": \"left\"})"
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   "id": "5d1e8469-e307-4136-a794-02b404de9756",
   "metadata": {},
   "source": [
    "```{note}\n",
    "Do not worry about the code and syntax for now. \n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ec41e07b-5c3b-4a44-ad64-519c9dc4bda7",
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    {
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       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_25bfd_level0_col0\" class=\"col_heading level0 col0\" >sms</th>\n",
       "      <th id=\"T_25bfd_level0_col1\" class=\"col_heading level0 col1\" >spam</th>\n",
       "      <th id=\"T_25bfd_level0_col2\" class=\"col_heading level0 col2\" >spam_predictions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_25bfd_level0_row0\" class=\"row_heading level0 row0\" >3245</th>\n",
       "      <td id=\"T_25bfd_row0_col0\" class=\"data row0 col0\" >Funny fact Nobody teaches volcanoes 2 erupt, tsunamis 2 arise, hurricanes 2 sway aroundn no 1 teaches hw 2 choose a wife Natural disasters just happens</td>\n",
       "      <td id=\"T_25bfd_row0_col1\" class=\"data row0 col1\" >ham</td>\n",
       "      <td id=\"T_25bfd_row0_col2\" class=\"data row0 col2\" >ham</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_25bfd_level0_row1\" class=\"row_heading level0 row1\" >944</th>\n",
       "      <td id=\"T_25bfd_row1_col0\" class=\"data row1 col0\" >I sent my scores to sophas and i had to do secondary application for a few schools. I think if you are thinking of applying, do a research on cost also. Contact joke ogunrinde, her school is one me the less expensive ones</td>\n",
       "      <td id=\"T_25bfd_row1_col1\" class=\"data row1 col1\" >ham</td>\n",
       "      <td id=\"T_25bfd_row1_col2\" class=\"data row1 col2\" >ham</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_25bfd_level0_row2\" class=\"row_heading level0 row2\" >1044</th>\n",
       "      <td id=\"T_25bfd_row2_col0\" class=\"data row2 col0\" >We know someone who you know that fancies you. Call 09058097218 to find out who. POBox 6, LS15HB 150p</td>\n",
       "      <td id=\"T_25bfd_row2_col1\" class=\"data row2 col1\" >spam</td>\n",
       "      <td id=\"T_25bfd_row2_col2\" class=\"data row2 col2\" >spam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_25bfd_level0_row3\" class=\"row_heading level0 row3\" >2484</th>\n",
       "      <td id=\"T_25bfd_row3_col0\" class=\"data row3 col0\" >Only if you promise your getting out as SOON as you can. And you'll text me in the morning to let me know you made it in ok.</td>\n",
       "      <td id=\"T_25bfd_row3_col1\" class=\"data row3 col1\" >ham</td>\n",
       "      <td id=\"T_25bfd_row3_col2\" class=\"data row3 col2\" >ham</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f10744dffd0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_dict = {\n",
    "    \"sms\": X_test[0:4],\n",
    "    \"spam\": y_test[0:4],  # actual spam\n",
    "    \"spam_predictions\": clf.predict(X_test[0:4]),\n",
    "}\n",
    "pred_df = pd.DataFrame(pred_dict)\n",
    "pred_df.style.set_properties(**{\"text-align\": \"left\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a097504-cfaa-4ad1-9911-78a93ab4b3ba",
   "metadata": {},
   "source": [
    "**We have accurately predicted labels for the unseen text messages above!**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f732497a-8cf9-40fc-8ee5-7f991bac314c",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "212f3d9a-87d1-482a-87de-ef52974ecbbf",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### (Supervised) machine learning: popular definition \n",
    "<blockquote>\n",
    "A field of study that gives computers the ability to learn without being explicitly programmed. <br> -- Arthur Samuel (1959)\n",
    "</blockquote>\n",
    "\n",
    "ML is a different way to think about problem solving.\n",
    "\n",
    "![](img/traditional-programming-vs-ML.png)\n",
    "<!-- <img src=\"img/traditional-programming-vs-ML.png\" height=\"700\" width=\"700\">  -->"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ecf610e-1da9-4331-8884-7c7c0a70b85e",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Examples\n",
    "\n",
    "Let's look at some concrete examples of supervised machine learning. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09ef1355-a85b-406a-9fcb-c730da77d28e",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "Do not worry about the code at this point. Just focus on the input and output in each example.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e6ba6a2-012a-445f-8787-abc1e9d7a800",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### Example 1: Predicting whether a patient has a liver disease or not"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "928773b1-d9a0-4197-9933-6bc803e0a123",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "##### Input data\n",
    "\n",
    "Suppose we are interested in predicting whether a patient has the disease or not. We are given some tabular data with inputs and outputs of liver patients, as shown below. The data contains a number of input features and a special column called \"Target\" which is the output we are interested in predicting. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99bb7174-190b-4fbd-9f58-f66818a608ad",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "Download the data from [here](https://www.kaggle.com/uciml/indian-liver-patient-records). \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "86996f4a-2365-40d7-b3d0-cb67f511ee31",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Total_Bilirubin</th>\n",
       "      <th>Direct_Bilirubin</th>\n",
       "      <th>Alkaline_Phosphotase</th>\n",
       "      <th>Alamine_Aminotransferase</th>\n",
       "      <th>Aspartate_Aminotransferase</th>\n",
       "      <th>Total_Protiens</th>\n",
       "      <th>Albumin</th>\n",
       "      <th>Albumin_and_Globulin_Ratio</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>268</th>\n",
       "      <td>40</td>\n",
       "      <td>14.5</td>\n",
       "      <td>6.4</td>\n",
       "      <td>358</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.50</td>\n",
       "      <td>Disease</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>33</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>256</td>\n",
       "      <td>21</td>\n",
       "      <td>30</td>\n",
       "      <td>8.5</td>\n",
       "      <td>3.9</td>\n",
       "      <td>0.80</td>\n",
       "      <td>Disease</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>24</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>188</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>5.5</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.71</td>\n",
       "      <td>No Disease</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>60</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>171</td>\n",
       "      <td>31</td>\n",
       "      <td>26</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.00</td>\n",
       "      <td>No Disease</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>18</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.2</td>\n",
       "      <td>199</td>\n",
       "      <td>34</td>\n",
       "      <td>31</td>\n",
       "      <td>6.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.16</td>\n",
       "      <td>No Disease</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Age  Total_Bilirubin  Direct_Bilirubin  Alkaline_Phosphotase  \\\n",
       "268   40             14.5               6.4                   358   \n",
       "356   33              0.7               0.2                   256   \n",
       "110   24              0.7               0.2                   188   \n",
       "488   60              0.7               0.2                   171   \n",
       "132   18              0.8               0.2                   199   \n",
       "\n",
       "     Alamine_Aminotransferase  Aspartate_Aminotransferase  Total_Protiens  \\\n",
       "268                        50                          75             5.7   \n",
       "356                        21                          30             8.5   \n",
       "110                        11                          10             5.5   \n",
       "488                        31                          26             7.0   \n",
       "132                        34                          31             6.5   \n",
       "\n",
       "     Albumin  Albumin_and_Globulin_Ratio      Target  \n",
       "268      2.1                        0.50     Disease  \n",
       "356      3.9                        0.80     Disease  \n",
       "110      2.3                        0.71  No Disease  \n",
       "488      3.5                        1.00  No Disease  \n",
       "132      3.5                        1.16  No Disease  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"data/indian_liver_patient.csv\")\n",
    "df = df.drop(columns = [\"Gender\"])\n",
    "df[\"Dataset\"] = df[\"Dataset\"].replace(1, \"Disease\")\n",
    "df[\"Dataset\"] = df[\"Dataset\"].replace(2, \"No Disease\")\n",
    "df.rename(columns={\"Dataset\": \"Target\"}, inplace=True)\n",
    "train_df, test_df = train_test_split(df, test_size=4, random_state=42)\n",
    "train_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4427867-3135-45ec-b850-526d3a502317",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "##### Building a supervise machine learning model\n",
    "\n",
    "Let's train a supervised machine learning model with the input and output above. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e82be94f-e169-41e7-93a4-124f692c82d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "from lightgbm.sklearn import LGBMClassifier\n",
    "\n",
    "X_train = train_df.drop(columns=[\"Target\"])\n",
    "y_train = train_df[\"Target\"]\n",
    "X_test = test_df.drop(columns=[\"Target\"])\n",
    "y_test = test_df[\"Target\"]\n",
    "model = LGBMClassifier(random_state=123)\n",
    "model.fit(X_train, y_train);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e68d5fa1-2c73-4a99-9fc4-51bec777bf2a",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "##### Model predictions on unseen data\n",
    "\n",
    "- Given features of new patients below we'll use this model to predict whether these patients have the liver disease or not. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "df5916f4-c4c1-4a9d-b3ab-db7ca5b01f56",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Predicted_target</th>\n",
       "      <th>Age</th>\n",
       "      <th>Total_Bilirubin</th>\n",
       "      <th>Direct_Bilirubin</th>\n",
       "      <th>Alkaline_Phosphotase</th>\n",
       "      <th>Alamine_Aminotransferase</th>\n",
       "      <th>Aspartate_Aminotransferase</th>\n",
       "      <th>Total_Protiens</th>\n",
       "      <th>Albumin</th>\n",
       "      <th>Albumin_and_Globulin_Ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No Disease</td>\n",
       "      <td>19</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.8</td>\n",
       "      <td>178</td>\n",
       "      <td>13</td>\n",
       "      <td>26</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>1.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Disease</td>\n",
       "      <td>12</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>719</td>\n",
       "      <td>157</td>\n",
       "      <td>108</td>\n",
       "      <td>7.2</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Disease</td>\n",
       "      <td>60</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2.8</td>\n",
       "      <td>214</td>\n",
       "      <td>412</td>\n",
       "      <td>850</td>\n",
       "      <td>7.3</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Disease</td>\n",
       "      <td>42</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>162</td>\n",
       "      <td>155</td>\n",
       "      <td>108</td>\n",
       "      <td>8.1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.90</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Predicted_target  Age  Total_Bilirubin  Direct_Bilirubin  \\\n",
       "0       No Disease   19              1.4               0.8   \n",
       "1          Disease   12              1.0               0.2   \n",
       "2          Disease   60              5.7               2.8   \n",
       "3          Disease   42              0.5               0.1   \n",
       "\n",
       "   Alkaline_Phosphotase  Alamine_Aminotransferase  Aspartate_Aminotransferase  \\\n",
       "0                   178                        13                          26   \n",
       "1                   719                       157                         108   \n",
       "2                   214                       412                         850   \n",
       "3                   162                       155                         108   \n",
       "\n",
       "   Total_Protiens  Albumin  Albumin_and_Globulin_Ratio  \n",
       "0             8.0      4.6                        1.30  \n",
       "1             7.2      3.7                        1.00  \n",
       "2             7.3      3.2                        0.78  \n",
       "3             8.1      4.0                        0.90  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_df = pd.DataFrame({\"Predicted_target\": model.predict(X_test).tolist()})\n",
    "\n",
    "df_concat = pd.concat([pred_df, X_test.reset_index(drop=True)], axis=1)\n",
    "df_concat"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc973f4b-00fa-4f35-a0c7-29d21cb97fed",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "243bd5b3-2383-4426-a346-87dd5c61af42",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### Example 2: Predicting the label of a given image \n",
    "\n",
    "Suppose you want to predict the label of a given image using supervised machine learning. We are using a pre-trained model here to predict labels of new unseen images. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "61d0d419-54e3-4265-bcda-864dcb956bcb",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                         Class  Probability score\n",
      "                     tiger cat              0.357\n",
      "              tabby, tabby cat              0.207\n",
      "               lynx, catamount              0.049\n",
      "Pembroke, Pembroke Welsh corgi              0.046\n",
      "--------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                   Class  Probability score\n",
      "                                 macaque              0.714\n",
      "patas, hussar monkey, Erythrocebus patas              0.122\n",
      "      proboscis monkey, Nasalis larvatus              0.098\n",
      "                   guenon, guenon monkey              0.017\n",
      "--------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                     Class  Probability score\n",
      "         cheetah, chetah, Acinonyx jubatus              0.982\n",
      "                  leopard, Panthera pardus              0.012\n",
      "jaguar, panther, Panthera onca, Felis onca              0.004\n",
      "       snow leopard, ounce, Panthera uncia              0.001\n",
      "--------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                        Class  Probability score\n",
      "Walker hound, Walker foxhound              0.577\n",
      "                  EntleBucher              0.089\n",
      "             English foxhound              0.086\n",
      "                       beagle              0.063\n",
      "--------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "from PIL import Image\n",
    "\n",
    "# Predict labels with associated probabilities for unseen images\n",
    "images = glob.glob(\"data/test_images/*.*\")\n",
    "for image in images:\n",
    "    img = Image.open(image)\n",
    "    img.load()\n",
    "    plt.imshow(img)\n",
    "    plt.show()\n",
    "    df = classify_image(img)\n",
    "    print(df.to_string(index=False))\n",
    "    print(\"--------------------------------------------------------------\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ef72ad4-d842-4cec-a2a9-fbf67fd0e8d5",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecf75098-7c3e-45b9-8073-318baf500003",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### Example 3: Predicting sentiment expressed in a movie review\n",
    "\n",
    "Suppose you are interested in predicting whether a given movie review is positive or negative. You can do it using supervised machine learning. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "481fdad0-5006-4384-a0cb-0c5090b8133b",
   "metadata": {},
   "source": [
    "Download the data from [here](https://www.kaggle.com/utathya/imdb-review-dataset). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3bc2a175-d33f-4c36-9cb1-6effc877abad",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_56c83_row0_col0, #T_56c83_row0_col1, #T_56c83_row1_col0, #T_56c83_row1_col1, #T_56c83_row2_col0, #T_56c83_row2_col1, #T_56c83_row3_col0, #T_56c83_row3_col1, #T_56c83_row4_col0, #T_56c83_row4_col1 {\n",
       "  text-align: left;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_56c83\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_56c83_level0_col0\" class=\"col_heading level0 col0\" >review</th>\n",
       "      <th id=\"T_56c83_level0_col1\" class=\"col_heading level0 col1\" >target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_56c83_level0_row0\" class=\"row_heading level0 row0\" >17812</th>\n",
       "      <td id=\"T_56c83_row0_col0\" class=\"data row0 col0\" >It may have been inevitable that with the onslaught of \"slasher\" movies in the early 1980's, that a few good ones might slip through the cracks. This is a great \"rare\" film from Jeff Lieberman, who insured his cult status with his memorable 1970's films \"Squirm\" and \"Blue Sunshine\".<br /><br />Five young people head into the Oregon mountains (this movie was actually shot on location) to do some camping and check out the deed to some land that one of them has acquired. Before long, they will predictably be terrorized by a bulky killer with an incredibly creepy wheezing laugh.<br /><br />\"Just Before Dawn\" is noticeably more ambitious, \"arty\", and intelligent than some slasher films. Lieberman actually fleshes out the characters - well, two of them, anyway - as much as a 90-minute-long film will allow him. The film has genuine moments of suspense and tension, and actually refrains from graphic gore, save for one killing right at the beginning.<br /><br />There is an above-average cast here, including Oscar winner George Kennedy, as a forest ranger who's understandably gone a little flaky from having been alone in the wilderness for too long. Jack Lemmon's son Chris, future Brian De Palma regular Gregg Henry, blonde lead Deborah Benson (it's too bad she hasn't become a more well-known performer, judging by her work here), Ralph Seymour (\"Ghoulies\"), Mike Kellin (\"Sleepaway Camp\"), and Jamie Rose (\"Chopper Chicks in Zombietown\") round out the cast.<br /><br />Some of the shots are interesting, and the early music score by Brad Feidel (now best known for his \"Terminator\" theme) is haunting and atmospheric.<br /><br />This is worth catching for the important plot twist at about the one hour mark, although a moment at about 75 minutes in involving the heroine and a tree and the killer is almost comical; it may actually remind a viewer of a cartoon! One of the most clever touches is the final dispatching of the killer, which I'd never seen before in a horror film and probably won't see again.<br /><br />I didn't give it 10 out of 10 because I can't honestly that I was that frightened. Still, it's an interesting slasher that is worthy of re-discovery.<br /><br />\"That deed don't mean nothing, son. Those mountains can't read.\"<br /><br />9/10</td>\n",
       "      <td id=\"T_56c83_row0_col1\" class=\"data row0 col1\" >pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_56c83_level0_row1\" class=\"row_heading level0 row1\" >32212</th>\n",
       "      <td id=\"T_56c83_row1_col0\" class=\"data row1 col0\" >Tell the truth Iâ??m a bit stun to see all these positive review by so many people, which is also the main reason why I actually decide to see this movie. And after having seen it, I was really a disappointed, and this comes from the guy that loves this genre of movie.<br /><br />Iâ??m surprise at this movie all completely â?? it is like a kidâ??s movie with nudity for absolutely no reason and it all involve little children cursing and swearing. Iâ??m not at all righteous but this has really gone too far in my account.<br /><br />Synopsis: The story about two guys got send to the big brother program for their reckless behavior. There they met up with one kids with boobs obsession and the other is a medieval freak.<br /><br />Just the name it self is not really connected with the story at all. They are not being a role model and or do anything but to serve their time for what they have done. The story is very predictable (though expected) and the humor is lame. And havenâ??t we already seen the same characters (play by Mc Lovinâ??) in so many other movies (like Sasquatch Gang?). I think I laugh thrice and almost fell a sleep.<br /><br />Well the casting was alright after all he is the one that produce the screenplay. And the acting is so-so as expected when youâ??re watching this type of movie. And the direction, what do one expect? This is the same guy who brought us Wet Hot American Summer, and that movie also sucks. But somehow he always managed to bring in some star to attract his horrendous movie.<br /><br />Anyway I felt not total riff off but a completely waste of time. Only the naked scenes seem to be the best part in the movie. Canâ??t really see any point why I should recommend this to anyone.<br /><br />Pros: Elizabeth Bank? Two topless scenes.<br /><br />Cons: Not funny, dreadful story, nudity and kids do not mix together.<br /><br />Rating: 3.5/10 (Grade: F)</td>\n",
       "      <td id=\"T_56c83_row1_col1\" class=\"data row1 col1\" >neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_56c83_level0_row2\" class=\"row_heading level0 row2\" >14903</th>\n",
       "      <td id=\"T_56c83_row2_col0\" class=\"data row2 col0\" >After getting thrown out of their last job and finding employment scarce in the United Kingdom, the six members of the Wonder Boys, better known as The Crazy Gang see an advertisement for employment in the gold strike town of Red Gulch in the Yukon Territory. It's from a newspaper clipping and on the back there's a story about Chamberlain saying the country better be prepared for war. Off they go to the Yukon and The Frozen Limits.<br /><br />By the way, it's case of misplaced Chamberlains. The clipping is forty years old and it refers to Joe Chamberlain and the Boer War rather than Neville in the current crisis. But that's typical of how things go for this crew. I can see Stan Laurel making the same mistake.<br /><br />Of course when they get there it's a ghost town inhabited only by young Jean Kent and her grandfather Moore Marriott. He's getting on in years and is a bit touched in the head. Marriott's got a gold mine that he's misplaced somewhere that he goes to in his sleep, that is when he's sleepwalking. The Gang better help him find that mine or otherwise pretty Ms. Kent won't marry stalwart trapper Anthony Hulme, but rather saloon owner Bernard Lee, a fate worse than death.<br /><br />This was my first exposure to the Crazy Gang and I can see both why they were so acclaimed in the UK and why they never made any impact across the pond. The jokes come fast and furious and then were a number of things that the Code in the USA just wouldn't allow. The jokes are also strictly topical British and a lot just wouldn't be gotten over here.<br /><br />The sight gags are universal, the final chase scene is worthy of anything that the Marx Brothers did in America. My suggestion is that if you watch The Frozen Limits, tape it if you have a working familiarity with British history and run it two or three times just to make sure you pick up everything. It will be worth it.</td>\n",
       "      <td id=\"T_56c83_row2_col1\" class=\"data row2 col1\" >pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_56c83_level0_row3\" class=\"row_heading level0 row3\" >3689</th>\n",
       "      <td id=\"T_56c83_row3_col0\" class=\"data row3 col0\" >The plot for a movie such of this is a giveaway. How can you go wrong with a gay plot line and all the colors and music of India - a story like this writes itself. I'll watch most anything, but this was unwatchable. The sad thing is, the white folks are the most colorful in the film. Vanessa was a riot with a mouth like a sailor, and Jack was great eye candy, but everyone else was so boring. Saeed Jeffrey, who was exceptional in My Beautiful Landrette, did what he could but the story was so boring. The saving grace was really the background music, which made it OK to laugh at the film, instead of with the film, or not at all. There are many other better gay movies, ethnic movies, just plain movies. I give a lot of low budget movies a pass, but this shouldn't have been made, or should have been made by someone else.</td>\n",
       "      <td id=\"T_56c83_row3_col1\" class=\"data row3 col1\" >neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_56c83_level0_row4\" class=\"row_heading level0 row4\" >22214</th>\n",
       "      <td id=\"T_56c83_row4_col0\" class=\"data row4 col0\" >It is a damn good movie,with some surprising twists,a good cast and a great script. Only a couple of stupid bits,like the Rasta hit-man scene (This guy's a professional?) but that has been commented on already. The fact I had only heard one guy at work mention it before, and did not have many opinions or reviews to go on, made it even more entertaining. This gets a higher score than maybe some people think it deserves, but I have to factor in the low budget and the good effort from the cast. It sickens me that some movies get made whose budget equals the GDP of a small country,with a hyped up release,good reviews,an Oscar winning director and/or actors, and turn out to be so disappointing,with actors sleepwalking through their roles and uninspired directing,with predictable plot lines and a story with holes in it so big,Sandra Bullock could drive a bomb-loaded bus through it. (Examples in my opinion are The Terminal,Castaway,Matrix:Revolutions) Extra points are awarded for the wardrobe department choosing great clothes for the cast,especially Paulina Porizcova,who wears a rubber dress in one scene,and a jacket with \"c*nt\" on the back in large letters in another!A sex scene which shows off her tight ass and a good soundtrack are added bonuses! And PLEASE,enough with the Tarantino comparisons,this did not remind me of a Tarantino flick at all.... and Tarantino borrows virtually every idea he has ever had from other movies! Even if that is your opinion,are we saying once a certain film or book is written or directed one way,no-one can ever use the same ideas again? get real. This film has it's own style.</td>\n",
       "      <td id=\"T_56c83_row4_col1\" class=\"data row4 col1\" >pos</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f10254c5900>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb_df = pd.read_csv(\"data/imdb_master.csv\", encoding=\"ISO-8859-1\")\n",
    "imdb_df = imdb_df[imdb_df[\"label\"].str.startswith((\"pos\", \"neg\"))]\n",
    "imdb_df = imdb_df.drop(columns = [\"Unnamed: 0\", \"type\", \"file\"])\n",
    "imdb_df.rename(columns={\"label\": \"target\"}, inplace=True)\n",
    "train_df, test_df = train_test_split(imdb_df, test_size=0.10, random_state=123)\n",
    "train_df.head().style.set_properties(**{\"text-align\": \"left\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "fc98c6ce-0fa2-4645-94ae-5dd501a1d994",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "# Build an ML model\n",
    "X_train, y_train = train_df[\"review\"], train_df[\"target\"]\n",
    "X_test, y_test = test_df[\"review\"], test_df[\"target\"]\n",
    "\n",
    "clf = Pipeline(\n",
    "    [\n",
    "        (\"vect\", CountVectorizer(max_features=5000)),\n",
    "        (\"clf\", LogisticRegression(max_iter=5000)),\n",
    "    ]\n",
    ")\n",
    "clf.fit(X_train, y_train);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3f345969-880e-4453-a1bf-7ad78fe98755",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_b82cf_row0_col0, #T_b82cf_row0_col1, #T_b82cf_row1_col0, #T_b82cf_row1_col1, #T_b82cf_row2_col0, #T_b82cf_row2_col1, #T_b82cf_row3_col0, #T_b82cf_row3_col1 {\n",
       "  text-align: left;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_b82cf\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_b82cf_level0_col0\" class=\"col_heading level0 col0\" >reviews</th>\n",
       "      <th id=\"T_b82cf_level0_col1\" class=\"col_heading level0 col1\" >sentiment_predictions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_b82cf_level0_row0\" class=\"row_heading level0 row0\" >11872</th>\n",
       "      <td id=\"T_b82cf_row0_col0\" class=\"data row0 col0\" >You'll feel like you've experienced a vacation in Hell after you have sat down and watched this horrible TV movie. This movie is an exercise in over-acting (very bad over-acting) to situations that made out to be more than what they are. I won't give away the plot, but once you realize why the people in this film are running from the native man in the film you will demand the two wasted hours of your life back. The only plus is seeing Marcia Brady running around in a bikini!</td>\n",
       "      <td id=\"T_b82cf_row0_col1\" class=\"data row0 col1\" >neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_b82cf_level0_row1\" class=\"row_heading level0 row1\" >40828</th>\n",
       "      <td id=\"T_b82cf_row1_col0\" class=\"data row1 col0\" >Bela Lugosi gets to play one of his rare good guy roles in a serial based upon the long running radio hit (which was also the source of a feature film where Lugosi played the villain.) Lugosi cuts a fine dashing figure and its sad that he didn't get more roles where he could be the guy in command in a good way. Here Chandu returns from the East in order to help the Princess Nadji who is being hunted by the leaders of the cult of Ubasti who need her to bring back from the dead the high priestess of their cult. This is a good looking globe trotting serial that is a great deal of fun. To be certain the pacing is a bit slack, more akin to one of Principals (the producing studios) features then a rip roaring adventure, but it's still enjoyable. This plays better than the two feature films that were cut from it because it allows for things to happen at their own pace instead of feeling rushed or having a sense that \"hey I missed something\". One of the trilogy of three good serials Lugosi made, the others being SOS Coast Guard and Phantom Creeps</td>\n",
       "      <td id=\"T_b82cf_row1_col1\" class=\"data row1 col1\" >pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_b82cf_level0_row2\" class=\"row_heading level0 row2\" >36400</th>\n",
       "      <td id=\"T_b82cf_row2_col0\" class=\"data row2 col0\" >When you wish for the dragon to eat every cast member, you know you're in for a bad ride.<br /><br />I went in with very, very low expectations, having read some of the other comments, and was not let down. Unlike some other cheap and failed movies, however, this one doesn't really remain hilariously (and unintentionally) funny throughout.<br /><br />-SPOILERS FOLLOW-<br /><br />First of all, plot it very inconsistent. Looking past the \"small\" mistakes, such as the dragon growing up in 3 hours, the whole idea it's based on is messed up. See, the movie wants us to believe that dragons came from outer space in the form of meteorites which really were dragon eggs. After explaining this, they show some peasant poking at one with his pitchfork and the dragon pops out. Later, the obligatory \"crazy scientist\" guy babbles on about how dragons outlived the dinosaurs. So apparently humans were around when dinosaurs were, or we just have a fine little plot hole here. The other major thing is that the lab is blown up with a force \"half as strong\" as what was used for Hiroshima. Then two guys later walk in to check everything out, and it's almost unscathed! There's even another dragon, which grew out of who knows what. All in all it's very predictable. As soon as the guy mentioned cloning, I guessed they'd clone a dragon. That means that our Mr. Smarty-pants security guy isn't so intuitive and smart as the movie would have you believe, if you ignore that I knew this film would be about, you know, dragons.<br /><br />Putting that aside, the second worst thing is the \"special effects.\" Others have mentioned the fake rocks falling during the beginning, the CG helicopter, and the dragon. It looks a bit better than a blob, but it ruined whatever it had going for it when it trudged down the hall in the same manner time after time. To their credit, the flying dragons in the beginning looked OK from far away (although the one in the cave is probably the worst one in the whole movie.) These things are funny to watch, however. The scenes where a million different shots of the same person facing different ways are shown are not. Nor are the \"introduction\" screens with the vital stats.<br /><br />Coming to the actors, they weren't the greatest, but I guess at least they tried? They seemed more enthusiastic about what they were doing than many of the actors participating in the recent \"BloodRayne,\" for example, and you've got to give them points for that. One thing I noticed though was that the woman who plays Meredith often had her face covered in make-up that was many tones lighter than the rest of her. She looked like she had a bad run-in with some white-face.<br /><br />The script is bad and cheesy. You don't really notice the music, but it's actually not too bad for the most part.<br /><br />The bottom line is don't watch it unless you want to see it because you hear it's bad (like I did), although the only funny things are the bad CG effects. Other than that, don't waste your time and money.</td>\n",
       "      <td id=\"T_b82cf_row2_col1\" class=\"data row2 col1\" >neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_b82cf_level0_row3\" class=\"row_heading level0 row3\" >5166</th>\n",
       "      <td id=\"T_b82cf_row3_col0\" class=\"data row3 col0\" >Sorry, but Jacqueline Hyde (get it??? - Jack L and Hyde - Jekyll & Hyde) has some of the worst acting this side of hardcore porn, not to mention a script apparently written by a first-grader with undiagnosed learning disabilities.<br /><br />Jackie Hyde inherits an old mansion by a grandfather she never knew she had. Guess who? Yes, an inventor of the special formula that slowly takes over one's body and mind - yes, that Mr. Hyde! <br /><br />Despite some nice skin scenes, this film fails to register any feeling or emotion other than uncontrollable laughter.<br /><br />As much as poor Jackie tries she just can't stay away from granddaddy's special formula and the result is an hour and half of wasted time.</td>\n",
       "      <td id=\"T_b82cf_row3_col1\" class=\"data row3 col1\" >neg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f102862fb20>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Predict on unseen data using the built model\n",
    "pred_dict = {\n",
    "    \"reviews\": X_test[0:4],\n",
    "    \"sentiment_predictions\": clf.predict(X_test[0:4]),\n",
    "}\n",
    "pred_df = pd.DataFrame(pred_dict)\n",
    "pred_df.style.set_properties(**{\"text-align\": \"left\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10dad017-ca73-4833-a4cb-f3daea9ea909",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c0991b3-c911-4fb7-96bd-5214a488beac",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### Example 4: Predicting housing prices\n",
    "\n",
    "Suppose we want to predict housing prices given a number of attributes associated with houses. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54f23833-3765-425a-ae91-b2153bd6ff88",
   "metadata": {},
   "source": [
    "Download the data from [here](https://www.kaggle.com/harlfoxem/housesalesprediction). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6b42804c-09df-4905-bab9-0ed09090cc32",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>target</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>sqft_living</th>\n",
       "      <th>sqft_lot</th>\n",
       "      <th>floors</th>\n",
       "      <th>waterfront</th>\n",
       "      <th>view</th>\n",
       "      <th>condition</th>\n",
       "      <th>grade</th>\n",
       "      <th>sqft_above</th>\n",
       "      <th>sqft_basement</th>\n",
       "      <th>yr_built</th>\n",
       "      <th>yr_renovated</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>lat</th>\n",
       "      <th>long</th>\n",
       "      <th>sqft_living15</th>\n",
       "      <th>sqft_lot15</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8583</th>\n",
       "      <td>509000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1930</td>\n",
       "      <td>3521</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
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       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>1930</td>\n",
       "      <td>0</td>\n",
       "      <td>1989</td>\n",
       "      <td>0</td>\n",
       "      <td>98007</td>\n",
       "      <td>47.6092</td>\n",
       "      <td>-122.146</td>\n",
       "      <td>1840</td>\n",
       "      <td>3576</td>\n",
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       "    <tr>\n",
       "      <th>19257</th>\n",
       "      <td>675000.0</td>\n",
       "      <td>5</td>\n",
       "      <td>2.75</td>\n",
       "      <td>2570</td>\n",
       "      <td>12906</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
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       "      <td>8</td>\n",
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       "      <td>0</td>\n",
       "      <td>98075</td>\n",
       "      <td>47.5814</td>\n",
       "      <td>-122.050</td>\n",
       "      <td>2580</td>\n",
       "      <td>12927</td>\n",
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       "      <th>1295</th>\n",
       "      <td>420000.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1150</td>\n",
       "      <td>5120</td>\n",
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       "      <td>98116</td>\n",
       "      <td>47.5588</td>\n",
       "      <td>-122.392</td>\n",
       "      <td>1220</td>\n",
       "      <td>5120</td>\n",
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       "    <tr>\n",
       "      <th>15670</th>\n",
       "      <td>680000.0</td>\n",
       "      <td>8</td>\n",
       "      <td>2.75</td>\n",
       "      <td>2530</td>\n",
       "      <td>4800</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>1390</td>\n",
       "      <td>1140</td>\n",
       "      <td>1901</td>\n",
       "      <td>0</td>\n",
       "      <td>98112</td>\n",
       "      <td>47.6241</td>\n",
       "      <td>-122.305</td>\n",
       "      <td>1540</td>\n",
       "      <td>4800</td>\n",
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       "    <tr>\n",
       "      <th>3913</th>\n",
       "      <td>357823.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1240</td>\n",
       "      <td>9196</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>1240</td>\n",
       "      <td>0</td>\n",
       "      <td>1968</td>\n",
       "      <td>0</td>\n",
       "      <td>98072</td>\n",
       "      <td>47.7562</td>\n",
       "      <td>-122.094</td>\n",
       "      <td>1690</td>\n",
       "      <td>10800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         target  bedrooms  bathrooms  sqft_living  sqft_lot  floors  \\\n",
       "8583   509000.0         2       1.50         1930      3521     2.0   \n",
       "19257  675000.0         5       2.75         2570     12906     2.0   \n",
       "1295   420000.0         3       1.00         1150      5120     1.0   \n",
       "15670  680000.0         8       2.75         2530      4800     2.0   \n",
       "3913   357823.0         3       1.50         1240      9196     1.0   \n",
       "\n",
       "       waterfront  view  condition  grade  sqft_above  sqft_basement  \\\n",
       "8583            0     0          3      8        1930              0   \n",
       "19257           0     0          3      8        2570              0   \n",
       "1295            0     0          4      6         800            350   \n",
       "15670           0     0          4      7        1390           1140   \n",
       "3913            0     0          3      8        1240              0   \n",
       "\n",
       "       yr_built  yr_renovated  zipcode      lat     long  sqft_living15  \\\n",
       "8583       1989             0    98007  47.6092 -122.146           1840   \n",
       "19257      1987             0    98075  47.5814 -122.050           2580   \n",
       "1295       1946             0    98116  47.5588 -122.392           1220   \n",
       "15670      1901             0    98112  47.6241 -122.305           1540   \n",
       "3913       1968             0    98072  47.7562 -122.094           1690   \n",
       "\n",
       "       sqft_lot15  \n",
       "8583         3576  \n",
       "19257       12927  \n",
       "1295         5120  \n",
       "15670        4800  \n",
       "3913        10800  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"data/kc_house_data.csv\")\n",
    "df = df.drop(columns = [\"id\", \"date\"])\n",
    "df.rename(columns={\"price\": \"target\"}, inplace=True)\n",
    "train_df, test_df = train_test_split(df, test_size=0.2, random_state=4)\n",
    "train_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3c7669ee-891e-40d3-9d47-7b4e9d9e25b4",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/moveisi/miniconda3/envs/cpsc330/lib/python3.10/site-packages/xgboost/compat.py:36: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n",
      "/home/moveisi/miniconda3/envs/cpsc330/lib/python3.10/site-packages/xgboost/data.py:262: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  elif isinstance(data.columns, (pd.Int64Index, pd.RangeIndex)):\n"
     ]
    }
   ],
   "source": [
    "# Build a regression model\n",
    "import xgboost as xgb\n",
    "from xgboost import XGBRegressor\n",
    "\n",
    "X_train, y_train = train_df.drop(columns= [\"target\"]), train_df[\"target\"]\n",
    "X_test, y_test = test_df.drop(columns= [\"target\"]), train_df[\"target\"]\n",
    "\n",
    "model = XGBRegressor()\n",
    "model.fit(X_train, y_train);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "86257c76-3e64-4f1d-858b-3f9023f01773",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Predicted_target</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>sqft_living</th>\n",
       "      <th>sqft_lot</th>\n",
       "      <th>floors</th>\n",
       "      <th>waterfront</th>\n",
       "      <th>view</th>\n",
       "      <th>condition</th>\n",
       "      <th>grade</th>\n",
       "      <th>sqft_above</th>\n",
       "      <th>sqft_basement</th>\n",
       "      <th>yr_built</th>\n",
       "      <th>yr_renovated</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>lat</th>\n",
       "      <th>long</th>\n",
       "      <th>sqft_living15</th>\n",
       "      <th>sqft_lot15</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>333981.6250</td>\n",
       "      <td>4</td>\n",
       "      <td>2.25</td>\n",
       "      <td>2130</td>\n",
       "      <td>8078</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>1380</td>\n",
       "      <td>750</td>\n",
       "      <td>1977</td>\n",
       "      <td>0</td>\n",
       "      <td>98055</td>\n",
       "      <td>47.4482</td>\n",
       "      <td>-122.209</td>\n",
       "      <td>2300</td>\n",
       "      <td>8112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>615222.4375</td>\n",
       "      <td>3</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2210</td>\n",
       "      <td>7620</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>2210</td>\n",
       "      <td>0</td>\n",
       "      <td>1994</td>\n",
       "      <td>0</td>\n",
       "      <td>98052</td>\n",
       "      <td>47.6938</td>\n",
       "      <td>-122.130</td>\n",
       "      <td>1920</td>\n",
       "      <td>7440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>329770.0625</td>\n",
       "      <td>4</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1800</td>\n",
       "      <td>9576</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>1800</td>\n",
       "      <td>0</td>\n",
       "      <td>1977</td>\n",
       "      <td>0</td>\n",
       "      <td>98045</td>\n",
       "      <td>47.4664</td>\n",
       "      <td>-121.747</td>\n",
       "      <td>1370</td>\n",
       "      <td>9576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>565091.6250</td>\n",
       "      <td>3</td>\n",
       "      <td>2.50</td>\n",
       "      <td>1580</td>\n",
       "      <td>1321</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>1080</td>\n",
       "      <td>500</td>\n",
       "      <td>2014</td>\n",
       "      <td>0</td>\n",
       "      <td>98107</td>\n",
       "      <td>47.6688</td>\n",
       "      <td>-122.402</td>\n",
       "      <td>1530</td>\n",
       "      <td>1357</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Predicted_target  bedrooms  bathrooms  sqft_living  sqft_lot  floors  \\\n",
       "0       333981.6250         4       2.25         2130      8078     1.0   \n",
       "1       615222.4375         3       2.50         2210      7620     2.0   \n",
       "2       329770.0625         4       1.50         1800      9576     1.0   \n",
       "3       565091.6250         3       2.50         1580      1321     2.0   \n",
       "\n",
       "   waterfront  view  condition  grade  sqft_above  sqft_basement  yr_built  \\\n",
       "0           0     0          4      7        1380            750      1977   \n",
       "1           0     0          3      8        2210              0      1994   \n",
       "2           0     0          4      7        1800              0      1977   \n",
       "3           0     2          3      8        1080            500      2014   \n",
       "\n",
       "   yr_renovated  zipcode      lat     long  sqft_living15  sqft_lot15  \n",
       "0             0    98055  47.4482 -122.209           2300        8112  \n",
       "1             0    98052  47.6938 -122.130           1920        7440  \n",
       "2             0    98045  47.4664 -121.747           1370        9576  \n",
       "3             0    98107  47.6688 -122.402           1530        1357  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Predict on unseen examples using the built model\n",
    "pred_df = pd.DataFrame(\n",
    "    # {\"Predicted target\": model.predict(X_test[0:4]).tolist(), \"Actual price\": y_test[0:4].tolist()}\n",
    "    {\"Predicted_target\": model.predict(X_test[0:4]).tolist()}\n",
    ")\n",
    "df_concat = pd.concat([pred_df, X_test[0:4].reset_index(drop=True)], axis=1)\n",
    "df_concat"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2105fe0-b32a-4c03-9eb4-e8f826cd2a55",
   "metadata": {},
   "source": [
    "To summarize, supervised machine learning can be used on a variety of problems and different kinds of data. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2c8abb4-ab28-497c-9eb3-e808519147ce",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8ce1ea7-4ec6-4c25-ac5b-5f13ca1a3ef5",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### 🤔 Eva's questions\n",
    "\n",
    "At this point, Eva is wondering about many questions. \n",
    "\n",
    "- How are we exactly \"learning\" whether a message is spam and ham? \n",
    "- What do you mean by \"learn without being explicitly programmed\"? The code has to be somewhere ... \n",
    "- Are we expected to get correct predictions for all possible messages? How does it predict the label for a message it has not seen before?  \n",
    "- What if the model mis-labels an unseen example? For instance, what if the model incorrectly predicts a non-spam as a spam? What would be the consequences? \n",
    "- How do we measure the success or failure of spam identification? \n",
    "- If you want to use this model in the wild, how do you know how reliable it is?  \n",
    "- Would it be useful to know how confident the model is about the predictions rather than just a yes or a no?\n",
    "\n",
    "It's great to think about these questions right now. But Eva has to be patient. By the end of this course you'll know answers to many of these questions!  \n",
    "\n",
    "![](img/eva-qm.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ee4d99f-76dc-41c4-967d-32344bab1344",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Machine learning workflow \n",
    "\n",
    "Supervised machine learning is quite flexible; it can be used on a variety of problems and different kinds of data. Here is a typical workflow of a supervised machine learning systems.  \n",
    "\n",
    "![](img/ml-workflow.png)\n",
    "\n",
    "<!-- <img src=\"img/ml-workflow.png\" height=\"800\" width=\"800\">  -->\n",
    "\n",
    "We will build machine learning pipelines in this course, focusing on some of the steps above. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c72b1d04-3709-4dc9-8d6f-daea0b7a4224",
   "metadata": {},
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b87a1677-3645-4f6d-bbd2-2f6ff48817c3",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Survey (~5 min)\n",
    "\n",
    "- Please complete the anonymous restaurant survey on Qualtrics [here](https://ubc.ca1.qualtrics.com/jfe/form/SV_73VuZiuwM1eDVrw).\n",
    "  - We will try to analyze this data set in the coming weeks. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b52fec7c-7db1-4952-a510-0335318b477f",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "<br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0804333-230f-4db7-8d4e-6b250c214205",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Break (5 min)\n",
    "\n",
    "![](img/eva-coffee.png)\n",
    "\n",
    "- We will try to take a 5-minute break half way through every class."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2bb61ff-844a-445c-8aae-1db566218f6f",
   "metadata": {},
   "source": [
    "<br><br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d19b3bc-2e6d-4c2a-a1e2-e421b0e8be1b",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## About this course"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51e758b6-8e05-42be-b2c4-014fa28f636b",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Course website "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a600a1a-b340-4d6f-90d9-f23f081472c6",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "[https://github.com/UBC-CS/cpsc330-2022s](https://github.com/UBC-CS/cpsc330-2022s) is the most important link. \n",
    "- Please read everything on there!\n",
    "- The Syllabus quiz will be available on Canvas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46429e91-5824-46f8-bf24-9ce35456a225",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "### CPSC 330 vs. 340\n",
    "\n",
    "Read [https://github.com/UBC-CS/cpsc330-2022s/blob/master/docs/330_vs_340.md](https://github.com/UBC-CS/cpsc330-2022s/blob/master/docs/330_vs_340.md)\n",
    "which explains the difference between two courses.  \n",
    "\n",
    "**TLDR:**\n",
    "\n",
    "- 340: how do ML models work?\n",
    "- 330: how do I use ML models?\n",
    "- CPSC 340 has many prerequisites. \n",
    "- CPSC 340 goes deeper but has a more narrow scope.\n",
    "- I think CPSC 330 will be more useful if you just plan to apply basic ML."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90a26e3f-f971-4cf2-a93d-de1bd021f56e",
   "metadata": {},
   "source": [
    "### Registration, waitlist and prerequisites"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e727e117-0784-410f-a04f-bde73c6dafb2",
   "metadata": {},
   "source": [
    "Please go through [this document](https://github.com/UBC-CS/cpsc330-2022s/blob/master/docs/course_info.md#registration) carefully before contacting me about these issues. Even then, I am very unlikely to be able to help with registration, waitlist or prerequisite issues."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba9b2c16-c34e-4330-85c5-773ed74c5e11",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Course format\n",
    "\n",
    "- In person lectures M/W/F at 9:30am (FSC 1005).\n",
    "- Sometimes there will be videos to watch before or during the lecture time. (I will let you know in advance if you are expected to watch videos before the class.)\n",
    "- First homework assignment is due **this coming Thursday**, May 19, at 6pm.\n",
    "- You must do the first homework assignment on your own.\n",
    "- I'm hoping you'll be able to work with partners on subsequent assignments - pending the technology side of things.\n",
    "- Weekly tutorials will be **office hour format** run by the TAs and are **completely optional**.\n",
    "  - You do not need to be registered in a tutorial.\n",
    "  - You can attend whatever tutorials or office hours your want, regardless of in which/whether you're registered.\n",
    "- To support hybrid learning, we are planning to hold at least one tutorial online each week. \n",
    "- We'll have one midterm and one final."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27b3d0e7-c162-486d-916d-9ffb4c23f147",
   "metadata": {},
   "source": [
    "### Course calendar\n",
    "\n",
    "Our course Calendar will be maintained on Canvas. Please make sure you check it on a regular basis."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ddfc521-1c47-4fcb-8878-96fd0f8b8e7f",
   "metadata": {},
   "source": [
    "### Course structure\n",
    "\n",
    "- Introduction\n",
    "- Part I: ML fundamentals and preprocessing \n",
    "  - midterm\n",
    "- Part II: Unsupervised learning, transfer learning, common special cases\n",
    "- Part III: Communication and ethics\n",
    "  - ML skills are not beneficial if you can't use them **responsibly** and **communicate** your results. In this module we'll talk about these aspects."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d66b85fe-a045-494e-9c71-1e564bf5fb44",
   "metadata": {},
   "source": [
    "### Code of conduct\n",
    "\n",
    "- Our main forum for getting help will be [Piazza](https://piazza.com/class/l2wy4l83juo5jo)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc012b7c-8853-41ab-9ab6-21655d105d4b",
   "metadata": {},
   "source": [
    "Please read [this entire document about asking for help](https://github.com/UBC-CS/cpsc330-2022s/blob/master/docs/asking_for_help.md).\n",
    "\n",
    "**TLDR:** Be nice."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3d5ad3e-0674-40c7-952f-667cda66834c",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Lecture and homework format: Jupyter notebooks\n",
    "\n",
    "- This document is a [Jupyter notebook](https://jupyter.org/), with file extension `.ipynb`.\n",
    "- Confusingly, \"Jupyter notebook\" is also the original application that opens `.ipynb` files - but has since been replaced by **Jupyter lab**.\n",
    "  - I am using Jupyter lab, some things might not work with the Jupyter notebook application.\n",
    "  - The course setup/install instructions include Jupyter lab.\n",
    "- Jupyter notebooks contain a mix of code, code output, markdown-formatted text (including LaTeX equations), and more.\n",
    "  - When you open a Jupyter notebook in one of these apps, the document is \"live\", meaning you can run the code.\n",
    "  - For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "453bbce3-884e-42fc-a4c2-6f1649a320fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d475a094-3541-4d80-b229-67dd72e101ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[9999, 2, 3]"
      ]
     },
     "execution_count": 18,
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   ],
   "source": [
    "x = [1, 2, 3]\n",
    "x[0] = 9999\n",
    "x"
   ]
  },
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    "- By default, Jupyter prints out the result of the last line of code, so you don't need as many `print` statements.\n",
    "- In addition to the \"live\" notebooks, Jupyter notebooks can be statically rendered in the web browser, e.g. [this](https://github.com/UBC-CS/cpsc330-2022s/blob/master/lectures/01_intro.ipynb).\n",
    "  - This can be convenient for quick read-only access, without needing to launch the Jupyter notebook/lab application.\n",
    "  - But you need to launch the app properly to interact with the notebooks.\n",
    "\n"
   ]
  },
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    "### Lecture style\n",
    "\n",
    "- Lots of code snippets in Jupyter.\n",
    "- There will be some [YouTube videos](https://www.youtube.com/channel/UC40oUwJPrUmhsYdURk8OjqA) to watch before or during the lecture. \n",
    "- We will also try to work on some questions and exercises together during the class. \n",
    "- All materials will be posted on the course website and [this Jupyter book](file:///Users/kvarada/CS/2021-22/330/cpsc330/_build/html/README.html). "
   ]
  },
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    "#### Lecture notes\n",
    "\n",
    "- All the lectures from last year are already [available on the course website](https://github.com/UBC-CS/cpsc330-2022s/tree/v2.0/lectures).\n",
    "- I cannot promise anything will stay the same from last year to this year, so read them in advance at your own risk.\n",
    "- A \"finalized\" version will be pushed to [GitHub](https://github.com/UBC-CS/cpsc330-2022s) \n",
    "- There a [Jupyter book](https://ubc-cs.github.io/cpsc330/README.html) version available from last year as well."
   ]
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    "### Grades\n",
    "\n",
    "- The grading breakdown is [here](https://github.com/UBC-CS/cpsc330-2022s/blob/master/docs/course_info.md#grading). \n",
    "- The policy on challenging grades is [here](https://github.com/UBC-CS/cpsc330-2022s/blob/master/docs/grades.md)."
   ]
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   "source": [
    "## Setting up your computer for the course "
   ]
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    "### Recommended browser\n",
    "\n",
    "- I'll test the course notebooks and exams, which we'll be doing via [Canvas](https://canvas.ubc.ca/courses/78046), on the following two browsers: Chrome and Firefox. So I recommend that you use one of these browsers for the course.\n",
    "\n",
    "- You can install Chrome [here](https://www.google.com/chrome/). \n",
    "- You can install Firefox [here](https://www.mozilla.org/en-US/firefox/new/). "
   ]
  },
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    "### Activity\n",
    "\n",
    "In this course, we will primarily be using Python, git, GitHub, Canvas, Gradescope, and Piazza. Let's set up your computers for the course. \n",
    "\n",
    "- Follow the setup instructions [here](https://ubc-cs.github.io/cpsc330/docs/setup.html) to create a course conda environment on your computer. \n",
    "- If you do not have your computer with you, you can partner up with someone and set up your own computer later.  \n",
    "- We are available to answer your questions."
   ]
  },
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    "### Python requirements/resources\n",
    "\n",
    "We will primarily use Python in this course.\n",
    "\n",
    "Here is the basic Python knowledge you'll need for the course: \n",
    "\n",
    "- Basic Python programming\n",
    "- Numpy\n",
    "- Pandas\n",
    "- Basic matplotlib\n",
    "- Sparse matrices\n",
    "\n",
    "Some of you will already know Python, others won't. Homework 1 is all about Python.\n"
   ]
  },
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   "source": [
    "We do not have time to teach all the Python we need \n",
    "but you can find some useful Python resources [here](https://github.com/UBC-CS/cpsc330-2022s/blob/master/docs/resources.md).  \n"
   ]
  },
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    "<br><br>"
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   "source": [
    "### Checklist for you before the next class\n",
    "\n",
    "- [ ] Are you able to access course [Canvas](https://canvas.ubc.ca/courses/78046) shell? \n",
    "- [ ] Are you able to access [Gradescope](https://www.gradescope.ca/courses/5032)? (If not, refer to the [Gradescope Student Guide](https://lthub.ubc.ca/guides/gradescope-student-guide/).)\n",
    "- [ ] Are you able to access [course Piazza](https://piazza.com/class/l2wy4l83juo5jo)?\n",
    "- [ ] Did you follow the setup instructions [here](https://ubc-cs.github.io/cpsc330/docs/setup.html) to create a course conda environment on your computer?\n",
    "- [ ] Did you complete the anonymous [restaurant survey on Qualtrics](https://ubc.ca1.qualtrics.com/jfe/form/SV_73VuZiuwM1eDVrw)?\n",
    "- [ ] Did you complete the syllabus quiz on Canvas?\n",
    "  - It'll be released tomorrow"
   ]
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    "## Summary\n",
    "\n",
    "- Machine learning is a different paradigm for problem solving.    \n",
    "- Very often it reduces the time you spend programming and helps customizing and scaling your products. \n",
    "- In supervised learning we are given a set of observations ($X$) and their corresponding targets ($y$) and we wish to find a model function $f$ that relates $X$ to $y$.\n",
    "- You should be ready with the technology stack on your laptop now. If you were not able to do it during lecture time or you ran into trouble, post on Piazza or attend one of the tutorials or office hours. \n",
    "- Carefully read the course website. Make sure to complete the survey.\n",
    "- **The teaching team is here to help you learn the material and succeed in the course!**\n",
    "- Let's have fun learning this material together!\n"
   ]
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   "source": [
    "![](img/eva-seeyou.png)"
   ]
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