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    "# Loading/storing/converting data in `aeon`\n",
    "\n",
    "Getting data into the correct data structure is fundamental. These notebooks cover:\n",
    "\n",
    "1. [Data structures and containers for aeon estimators](data_structures.ipynb)\n",
    "\n",
    "`aeon` includes algorithms for time series forecasting and machine learning. These two\n",
    "communities have different conventions on how to store data and what to call data\n",
    "structures. The [data structures and containers notebook](data_structures.ipynb) goes\n",
    "into more detail as to how we store data, with recommendations on what to use for \n",
    "different learning tasks.\n",
    "\n",
    "2. [Converting from one data structure to another](data_conversions.ipynb)\n",
    "\n",
    "`aeon` provides tools from converting from one data structure to another. Estimators\n",
    "internally handle conversion to the one they need internally. The [data conversions\n",
    "notebook](data_conversions.ipynb) provides an overview of these conversions.\n",
    "\n",
    "3. [Loading data from file](data_loading.ipynb)\n",
    "\n",
    "`aeon` provides functions to load data directly from text files in several formats. The\n",
    "[data loading notebook](data_loading.ipynb) describes the formats of our\n",
    "supported files and how to load them into aeon data structures.\n",
    "\n",
    "4. [Provided datasets](provided_data.ipynb)\n",
    "\n",
    "`aeon` ships with a range of datasets used in examples and testing. The [provided\n",
    "datasets notebook](provided_data.ipynb) describes all these datasets.\n",
    "\n",
    "5. [Loading data from online repositories](benchmarking_data.ipynb).\n",
    "\n",
    "You can load data directly from the [Time Series Machine Learning\n",
    "archive](https://timeseriesclassification.com/) and the \n",
    "[Monash time series forecasting](https://forecastingdata.org/) \n",
    "sites. More details in the [load from web notebook](load_data_from_web.ipynb)."
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