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@@ -45,7 +45,7 @@ For more details, please refer to our paper ["Qlib: An AI-oriented Quantitative
- [Data Preparation](#data-preparation)
- [Auto Quant Research Workflow](#auto-quant-research-workflow)
- [Building Customized Quant Research Workflow by Code](#building-customized-quant-research-workflow-by-code)
- [**Quant Model Zoo**](#quant-model-zoo)
- [**Quant Model(Paper) Zoo**](#quant-model(paper)-zoo)
- [Run a single model](#run-a-single-model)
- [Run multiple models](#run-multiple-models)
- [**Quant Dataset Zoo**](#quant-dataset-zoo)
@@ -276,7 +276,7 @@ Qlib provides a tool named `qrun` to run the whole workflow automatically (inclu
The automatic workflow may not suit the research workflow of all Quant researchers. To support a flexible Quant research workflow, Qlib also provides a modularized interface to allow researchers to build their own workflow by code. [Here](examples/workflow_by_code.ipynb) is a demo for customized Quant research workflow by code.
# [Quant Model Zoo](examples/benchmarks)
# [Quant Model(Paper) Zoo](examples/benchmarks)
Here is a list of models built on `Qlib`.
- [GBDT based on XGBoost (Tianqi Chen, et al. KDD 2016)](qlib/contrib/model/xgboost.py)