{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# todo: export the model from train.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# todo: copy import from train.ipynb\n",
    "# todo: copy normalize() from train.ipynb\n",
    "# todo: copy predict() from train.ipynb\n",
    "\n",
    "# todo: inject saved model into predict()\n",
    "# todo: turn predict() into a GreatAI service\n",
    "\n",
    "# todo: log prediction into output trace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if __name__ == '__main__':\n",
    "    # todo: add integration test (copy metric derivation from train.ipynb)\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# todo: serve prediction model\n",
    "# todo: open dashboard"
   ]
  }
 ],
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   "display_name": "Python 3.10.4 64-bit",
   "language": "python",
   "name": "python3"
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   "codemirror_mode": {
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "vscode": {
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