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Add alternatives to README
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README.md

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@@ -43,3 +43,26 @@ julia> y_test_pred = svmpredict(model, X_test);
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julia> accuracy = mean(y_test .== y_test_pred)
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0.8529411764705882
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```
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# Alternatives
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## Graph Kernels
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### Python
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- [GraKeL](https://github.com/ysig/GraKeL), A scikit-learn compatible library for graph kernels
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- [graphkit-learn](https://github.com/jajupmochi/graphkit-learn), A Python package for graph kernels, graph edit distances and graph pre-image problem.
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## General graph machine learning
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### Julia
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- [GeometricFlux](Geometric Deep Learning for Flux ), Geometric Deep Learning for Flux
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### Python
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- [StellarGraph](https://github.com/stellargraph/stellargraph), Machine Learning on Graphs
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- [DGL](https://github.com/dmlc/dgl), Python package built to ease deep learning on graph, on top of existing DL frameworks.
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- [Graph Nets](https://github.com/deepmind/graph_nets), Build Graph Nets in Tensorflow
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- [Spektral](https://github.com/danielegrattarola/spektral/), Graph Neural Networks with Keras and Tensorflow 2.
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- [PyTorch Geometric](https://github.com/rusty1s/pytorch_geometric), Geometric Deep Learning Extension Library for PyTorch

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