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Copy file name to clipboardExpand all lines: tutorial_nbs/15_PatchTST_a_new_transformer_for_LTSF.ipynb
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"id": "892a35dd",
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"metadata": {},
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"<a href=\"https://colab.research.google.com/github/timeseriesAI/tsai/blob/master/tutorial_nbs/15_PatchTST_a_new_transformer_for_long_term_multivariate_forecasting.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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"<a href=\"https://colab.research.google.com/github/timeseriesAI/tsai/blob/master/tutorial_nbs/15_PatchTST_a_new_transformer_for_LTSF.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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"cell_type": "markdown",
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""
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"cell_type": "markdown",
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"We'll approach the time series forecasting task as a supervised learning problem. Remember that `tsai` requires that both inputs and outputs have the following shape: \n",
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"To get those inputs and outputs we're going to use a function called `prepare_forecasting_data` that applies a sliding window along the dataframe:\n",
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