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    "# Setting up Python for Machine Learning: scikit-learn and Jupyter Notebook ([video #2](https://www.youtube.com/watch?v=IsXXlYVBt1M&list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A&index=2))\n",
    "\n",
    "Created by [Data School](https://www.dataschool.io). Watch all 10 videos on [YouTube](https://www.youtube.com/playlist?list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A). Download the notebooks from [GitHub](https://github.com/justmarkham/scikit-learn-videos).\n",
    "\n",
    "**Note:** Since the video recording, the official name of the \"IPython Notebook\" was changed to \"Jupyter Notebook\". However, the functionality is the same."
   ]
  },
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   "metadata": {},
   "source": [
    "## Agenda\n",
    "\n",
    "- What are the benefits and drawbacks of scikit-learn?\n",
    "- How do I install scikit-learn?\n",
    "- How do I use the Jupyter Notebook?\n",
    "- What are some good resources for learning Python?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![scikit-learn algorithm map](images/02_sklearn_algorithms.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Benefits and drawbacks of scikit-learn\n",
    "\n",
    "### Benefits:\n",
    "\n",
    "- **Consistent interface** to Machine Learning models\n",
    "- Provides many **tuning parameters** but with **sensible defaults**\n",
    "- Exceptional **documentation**\n",
    "- Rich set of functionality for **companion tasks**\n",
    "- **Active community** for development and support\n",
    "\n",
    "### Potential drawbacks:\n",
    "\n",
    "- Harder (than R) to **get started with Machine Learning**\n",
    "- Less emphasis (than R) on **model interpretability**\n",
    "\n",
    "### Further reading:\n",
    "\n",
    "- Ben Lorica: [Six reasons why I recommend scikit-learn](https://www.oreilly.com/content/six-reasons-why-i-recommend-scikit-learn/)\n",
    "- scikit-learn authors: [API design for machine learning software](https://arxiv.org/pdf/1309.0238v1.pdf)\n",
    "- Data School: [Should you teach Python or R for data science?](https://www.dataschool.io/python-or-r-for-data-science/)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![scikit-learn logo](images/02_sklearn_logo.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Installing scikit-learn\n",
    "\n",
    "**Option 1:** [Install scikit-learn library](https://scikit-learn.org/stable/install.html) and dependencies (NumPy and SciPy)\n",
    "\n",
    "**Option 2:** [Install Anaconda distribution](https://www.anaconda.com/products/individual) of Python, which includes:\n",
    "\n",
    "- Hundreds of useful packages (including scikit-learn)\n",
    "- IPython and Jupyter Notebook\n",
    "- conda package manager\n",
    "- Spyder IDE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Jupyter logo](images/02_jupyter_logo.svg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using the Jupyter Notebook\n",
    "\n",
    "### Components:\n",
    "\n",
    "- **IPython interpreter:** enhanced version of the standard Python interpreter\n",
    "- **Browser-based notebook interface:** weave together code, formatted text, and plots\n",
    "\n",
    "### Installation:\n",
    "\n",
    "- **Option 1:** [Install the Jupyter notebook](https://jupyter.readthedocs.io/en/latest/install.html) (includes IPython)\n",
    "- **Option 2:** Included with the Anaconda distribution\n",
    "\n",
    "### Launching the Notebook:\n",
    "\n",
    "- Type **jupyter notebook** at the command line to open the dashboard\n",
    "- Don't close the command line window while the Notebook is running\n",
    "\n",
    "### Keyboard shortcuts:\n",
    "\n",
    "**Command mode** (gray border)\n",
    "\n",
    "- Create new cells above (**a**) or below (**b**) the current cell\n",
    "- Navigate using the **up arrow** and **down arrow**\n",
    "- Convert the cell type to Markdown (**m**) or code (**y**)\n",
    "- See keyboard shortcuts using **h**\n",
    "- Switch to Edit mode using **Enter**\n",
    "\n",
    "**Edit mode** (green border)\n",
    "\n",
    "- **Ctrl+Enter** to run a cell\n",
    "- Switch to Command mode using **Esc**\n",
    "\n",
    "### IPython, Jupyter, and Markdown resources:\n",
    "\n",
    "- [nbviewer](https://nbviewer.jupyter.org/): view notebooks online as static documents\n",
    "- [IPython documentation](https://ipython.readthedocs.io/en/stable/)\n",
    "- [Jupyter Notebook quickstart](https://jupyter.readthedocs.io/en/latest/content-quickstart.html)\n",
    "- [GitHub's Mastering Markdown](https://guides.github.com/features/mastering-markdown/): short guide with lots of examples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Resources for learning Python\n",
    "\n",
    "- [Codecademy's Python course](https://www.codecademy.com/learn/learn-python): browser-based, tons of exercises\n",
    "- [DataQuest](https://www.dataquest.io/): browser-based, teaches Python in the context of data science\n",
    "- [Google's Python class](https://developers.google.com/edu/python/): slightly more advanced, includes videos and downloadable exercises (with solutions)\n",
    "- [Python for Everybody](https://www.py4e.com/): beginner-oriented book, includes slides and videos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comments or Questions?\n",
    "\n",
    "- Email: <kevin@dataschool.io>\n",
    "- Website: https://www.dataschool.io\n",
    "- Twitter: [@justmarkham](https://twitter.com/justmarkham)\n",
    "\n",
    "© 2021 [Data School](https://www.dataschool.io). All rights reserved."
   ]
  }
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