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    "# Tutorial Overview"
   ]
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   "source": [
    "The EarthML tutorial takes you through the various stages involved in using Python open-source tools to work with machine-learning and related data analysis tools for climate and other Earth science topics:\n",
    "\n",
    "1. [Data Ingestion](./01_Data_Ingestion.ipynb): Loading large data sets efficiently with [`intake`](https://github.com/ContinuumIO/intake).\n",
    "2. [Introduction to Visualization](./02_Introduction_to_Visualization.ipynb): How to visualize data loaded into memory.\n",
    "3. [Alignment and Preprocessing](./03_Alignment_and_Preprocessing.ipynb): How to prepare your data for the machine learning pipeline.\n",
    "4. [Machine Learning](./04_Machine_Learning.ipynb): Specifying a [`scikit-learn`](http://scikit-learn.org/stable/index.html) pipeline to ingest the prepared training data.\n",
    "5. [Data Visualization](./05_Data_Visualization.ipynb): How to visualize your data throughout the workflow, starting from data ingestion to the final machine learning product."
   ]
  }
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