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77
deploy.ipynb
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77
deploy.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# todo: export the model from train.ipynb"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# todo: copy import from train.ipynb\n",
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"# todo: copy normalize() from train.ipynb\n",
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"# todo: copy predict() from train.ipynb\n",
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"\n",
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"# todo: inject saved model into predict()\n",
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"# todo: turn predict() into a GreatAI service\n",
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"\n",
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"# todo: log prediction into output trace"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"if __name__ == '__main__':\n",
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" # todo: add integration test (copy metric derivation from train.ipynb)\n",
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" pass"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# todo: serve prediction model\n",
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"# todo: open dashboard"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.10.4 64-bit",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.4"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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