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Cllab update
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GilesStrong committed Dec 15, 2020
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Expand Up @@ -106,15 +106,15 @@ For an introduction and motivation for LUMIN, checkout this talk from IML-2019 a

Several examples are present in the form of Jupyter Notebooks in the `examples` folder. These can be run also on Google Colab to allow you to quickly try out the package.

1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.0/examples/Simple_Binary_Classification_of_earnings.ipynb) `examples/Simple_Binary_Classification_of_earnings.ipynb`: Very basic binary-classification example
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.0/examples/Binary_Classification_Signal_versus_Background.ipynb) `examples/Binary_Classification_Signal_versus_Background.ipynb`: Binary-classification example in a high-energy physics context
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.0/examples/Multiclass_Classification_Signal_versus_Backgrounds.ipynb) `examples/Multiclass_Classification_Signal_versus_Backgrounds.ipynb`: Multiclass-classification example in a high-energy physics context
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.0/examples/Single_Target_Regression_Di-Higgs_mass_prediction.ipynb) `examples/Single_Target_Regression_Di-Higgs_mass_prediction.ipynb`: Single-target regression example in a high-energy physics context
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.0/examples/Multi_Target_Regression_Di-tau_momenta.ipynb) `examples/Multi_Target_Regression_Di-tau_momenta.ipynb`: Multi-target regression example in a high-energy physics context
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.0/examples/Feature_Selection.ipynb) `examples/Feature_Selection.ipynb`: In-depth walkthrough for automated feature-selection
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.0/examples/Advanced_Model_Building.ipynb) `examples/Advanced_Model_Building.ipynb`: In-depth look at building more complicated models and a few advanced interpretation techniques
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.0/examples/Model_Exporting.ipynb) `examples/Model_Exporting.ipynb`: Walkthough for exporting a trained model to ONNX and TensorFlow
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.0/examples/RNNs_CNNs_and_GNNs_for_matrix_data.ipynb) `examples/RNNs_CNNs_and_GNNs_for_matrix_data.ipynb.ipynb`: Various examples of applying RNNs, CNNs, and GNNs to matrix data (top-tagging on jet constituents)
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.1/examples/Simple_Binary_Classification_of_earnings.ipynb) `examples/Simple_Binary_Classification_of_earnings.ipynb`: Very basic binary-classification example
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.1/examples/Binary_Classification_Signal_versus_Background.ipynb) `examples/Binary_Classification_Signal_versus_Background.ipynb`: Binary-classification example in a high-energy physics context
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.1/examples/Multiclass_Classification_Signal_versus_Backgrounds.ipynb) `examples/Multiclass_Classification_Signal_versus_Backgrounds.ipynb`: Multiclass-classification example in a high-energy physics context
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.1/examples/Single_Target_Regression_Di-Higgs_mass_prediction.ipynb) `examples/Single_Target_Regression_Di-Higgs_mass_prediction.ipynb`: Single-target regression example in a high-energy physics context
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.1/examples/Multi_Target_Regression_Di-tau_momenta.ipynb) `examples/Multi_Target_Regression_Di-tau_momenta.ipynb`: Multi-target regression example in a high-energy physics context
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.1/examples/Feature_Selection.ipynb) `examples/Feature_Selection.ipynb`: In-depth walkthrough for automated feature-selection
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.1/examples/Advanced_Model_Building.ipynb) `examples/Advanced_Model_Building.ipynb`: In-depth look at building more complicated models and a few advanced interpretation techniques
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.1/examples/Model_Exporting.ipynb) `examples/Model_Exporting.ipynb`: Walkthough for exporting a trained model to ONNX and TensorFlow
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.1/examples/RNNs_CNNs_and_GNNs_for_matrix_data.ipynb) `examples/RNNs_CNNs_and_GNNs_for_matrix_data.ipynb.ipynb`: Various examples of applying RNNs, CNNs, and GNNs to matrix data (top-tagging on jet constituents)

## Installation

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