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GilesStrong committed Mar 11, 2021
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# Targeting v0.7.2
# v0.7.2 - All your batch are belong to us - Micro Update

## Important changes

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19 changes: 10 additions & 9 deletions README.md
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Expand Up @@ -107,15 +107,16 @@ 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/v0.7.1/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)
1. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GilesStrong/lumin/blob/v0.7.2/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/v0.7.2/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/v0.7.2/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/v0.7.2/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/v0.7.2/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/v0.7.2/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/v0.7.2/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/v0.7.2/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/v0.7.2/examples/RNNs_CNNs_and_GNNs_for_matrix_data.ipynb) `examples/RNNs_CNNs_and_GNNs_for_matrix_data.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/v0.7.2/examples/Learning_To_Pivot.ipynb) `examples/Learning_To_Pivot.ipynb`: Example of adversarial training for parameter invariance

## Installation

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2 changes: 1 addition & 1 deletion build.md
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# Release Steps

1. Check scheduled depreceiations
1. Check scheduled depreciations
1. Run examples and fix errors
1. Check an example on Google Colab
1. Update readme and copy relevant information to docs/source/description.md
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