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  {
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   "source": [
    "# Cross Validation Tutorial\n",
    "\n",
    "Walk through k-fold experiments leveraging ModularML splitters and experiment tracking.\n",
    "Focus on reproducibility and how to aggregate metrics across folds.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1",
   "metadata": {},
   "source": [
    "## Scenario\n",
    "\n",
    "Describe the research question being addressed and why this workflow matters.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "Outline dataset prep, FeatureSet definitions, and experiment context initialization.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3",
   "metadata": {},
   "source": [
    "## Training\n",
    "\n",
    "Demonstrate how to assemble nodes, losses, optimizers, and training phases for this scenario.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4",
   "metadata": {},
   "source": [
    "## Evaluation\n",
    "\n",
    "Summarize metrics, qualitative checks, and how to inspect :class:`LossRecord` outputs.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5",
   "metadata": {},
   "source": [
    "## What’s Next\n",
    "\n",
    "Link to relevant how-to guides, explanations, or follow-up tutorials.\n"
   ]
  }
 ],
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