1_Setup.ipynb

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    "\n",
    "# 1. Setup\n",
    "Note: If you're already comfortable with `anaconda` and `jupyter notebook`, feel free to skip these steps and start the exercises. We'll be using `python 3.6.4` and `tensorflow 1.3.0`.\n",
    "\n",
    "## Installing Anaconda\n",
    "\n",
    "We will be using `anaconda` for this workshop. We highly recommend you do so for your own projects. `anaconda` is a \"tool box\" for ML; it comes with various libraries you need to do ML in python. Another neat thing about `anaconda` is that you can create a virtual environment, which is a separate python environment from the default one on your laptop. Virtual environments allow us to separate library dependencies across projects and make it easier for us to share our environment setups with other developers. In fact, we are going to do that right now!\n",
    "\n",
    "You can install Anaconda [here](https://www.anaconda.com/download). **Please download the `Python3.6` version.** Once you finished installing it run on your terminal:\n",
    "\n",
    "```\n",
    "conda -V\n",
    "```\n",
    "\n",
    "if you see the version of your conda (e.g. `5.0.1`), success! If not, google around and try hard to make it work...\n",
    "\n",
    "Even if you have `conda` installed already, make sure it is up-to-date. Run\n",
    "\n",
    "```\n",
    "conda update conda\n",
    "```\n",
    "\n",
    "## Setting up Jupyter\n",
    "\n",
    "First, [fork](https://help.github.com/articles/fork-a-repo/) this repository to your account.\n",
    "Second, open up your terminal and [`git clone`](https://help.github.com/articles/cloning-a-repository/) the forked repo to your laptop. If either of these don't work, click the link and read the github help page. Once you cloned, run the following:\n",
    "```\n",
    "conda env create environment.yml       # create conda virtual environment\n",
    "source activate tensorflow_workshop    # activate the virtual environment\n",
    "jupyter notebook                       # open jupyter on your default browser\n",
    "```\n",
    "\n",
    "The first line might take a while, but be patient.\n",
    "The last line should open the notebook on your default browser. Once you open `jupyter notebook`, make sure the kernel is set to `Python [conda env:tensorflow_workshop]`.\n",
    "\n",
    "![alt text](images/1_setup.png)\n",
    "\n",
    "Try opening some code in `3_Graphs_Sessions.ipynb`. If it successfully runs, great! Once you're done with your work, you can deactivate to get out of the virtual environment. Run on your terminal:\n",
    "```\n",
    "source deactivate                      # get out of the virtual environment\n",
    "```\n",
    "\n",
    "## You're all set!\n",
    "\n",
    "Now, you are ready to start writing some `tensorflow` code on `jupyter notebook` :)\n",
    "\n",
    "If you've never used `jupyter notebook` before, you might want to watch the following video:"
   ]
  },
  {
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   "execution_count": 1,
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   "outputs": [
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\n",
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"400\"\n",
       "            height=\"300\"\n",
       "            src=\"https://www.youtube.com/embed/HW29067qVWk\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.YouTubeVideo at 0x10c0f46a0>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.lib.display import YouTubeVideo\n",
    "YouTubeVideo('HW29067qVWk')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Whenever you want to sync your forked repo to ours...\n",
    "Run on your terminal:\n",
    "```\n",
    "# Add a separate remote repository from your forked one\n",
    "git remote add original git@github.com:kojino/CS282R_Deep_Learning_Workshop.git\n",
    "\n",
    "git pull original master\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:tensorflow_workshop]",
   "language": "python",
   "name": "conda-env-tensorflow_workshop-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}