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https://github.com/ajinkyat/deep_learning_entity_embeddings

Deep Learning and Entity Embeddings to predict driving behaviour and cluster accident hotspots
https://github.com/ajinkyat/deep_learning_entity_embeddings

deep-learning driving-behavior entity-embedding keras-tensorflow

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Deep Learning and Entity Embeddings to predict driving behaviour and cluster accident hotspots

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# Deep Learning and Entity Embeddings to predict driving behavior and cluster accident hotspots

This project repo is for Pune Smart City Hackathon organized by Niti Aayog (Planning Commision of India), Government of India

Check below Jupyter notebooks for solution overview.

Data cleaning and processing: [data_processing.ipynb](https://github.com/ajinkyaT/Deep_learning_Entity_Embeddings/blob/master/data_processing.ipynb)

Model architecture: [model_building.ipynb](https://github.com/ajinkyaT/Deep_learning_Entity_Embeddings/blob/master/model_building.ipynb)

Visualizing trained embeddings: [embedding_visualization.ipynb (Plotly visualizations are not rendered properly)](https://github.com/ajinkyaT/Deep_learning_Entity_Embeddings/blob/master/embedding_visualization.ipynb) instead download [embedding_visualization.html](https://github.com/ajinkyaT/Deep_learning_Entity_Embeddings/blob/master/embedding_visualization.html) and open it locally in the browser

Visualizing Route-Name Embeddings: [https://plot.ly/~ajinkyaT/5/](https://plot.ly/~ajinkyaT/5/)

Visualizing Stop-Name Embeddings: [https://plot.ly/~ajinkyaT/3/](https://plot.ly/~ajinkyaT/3/)

### Resources

- Guo, C., & Berkhahn, F. (2016). [Entity embeddings of categorical variables](https://arxiv.org/abs/1604.06737). arXiv preprint arXiv:1604.06737
- De Brébisson, A., Simon, É., Auvolat, A., Vincent, P., & Bengio, Y. (2015). [Artificial neural networks
applied to taxi destination prediction](https://arxiv.org/abs/1508.00021). arXiv preprint arXiv:1508.00021.