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Add demo
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@@ -61,7 +61,10 @@ At the module level, Qlib is a platform that consists of the above components. T
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This quick start guide tries to demonstrate
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1. It's very easy to build a complete Quant research workflow and try your ideas with _Qlib_.
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1. Though with *public data* and *simple models*, machine learning technologies **work very well** in practical Quant investment.
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2. Though with *public data* and *simple models*, machine learning technologies **work very well** in practical Quant investment.
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Here is a quick **[demo](https://terminalizer.com/view/3f24561a4470)** shows how to install ``Qlib``, and run LightGBM with ``qrun``. **But**, please make sure you have already prepared the data following the [instruction](#data-preparation).
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## Installation
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@@ -303,4 +306,4 @@ provided by the bot. You will only need to do this once across all repos using o
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This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
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For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or
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contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.
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contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.
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12
docs/_static/demo.sh
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12
docs/_static/demo.sh
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#!/bin/sh
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git clone https://github.com/microsoft/qlib.git
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cd qlib
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ls
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pip install pyqlib
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# or
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# pip install numpy
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# pip install --upgrade cython
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# python setup.py install
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cd examples
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ls
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qrun benchmarks/LightGBM/workflow_config_lightgbm_Alpha158.yaml
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