{"id":23503783,"url":"https://github.com/ajinkyat/deep_learning_entity_embeddings","last_synced_at":"2026-03-07T16:03:20.520Z","repository":{"id":124495216,"uuid":"146479710","full_name":"ajinkyaT/Deep_learning_Entity_Embeddings","owner":"ajinkyaT","description":"Deep Learning and Entity Embeddings to predict driving behaviour and cluster accident hotspots","archived":false,"fork":false,"pushed_at":"2018-10-24T03:08:20.000Z","size":32810,"stargazers_count":4,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-07-01T05:05:45.311Z","etag":null,"topics":["deep-learning","driving-behavior","entity-embedding","keras-tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ajinkyaT.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-08-28T17:02:09.000Z","updated_at":"2021-03-13T01:49:33.000Z","dependencies_parsed_at":null,"dependency_job_id":"9d8fa113-22ed-4dae-a9bf-a39f9dc0596e","html_url":"https://github.com/ajinkyaT/Deep_learning_Entity_Embeddings","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ajinkyaT/Deep_learning_Entity_Embeddings","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajinkyaT%2FDeep_learning_Entity_Embeddings","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajinkyaT%2FDeep_learning_Entity_Embeddings/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajinkyaT%2FDeep_learning_Entity_Embeddings/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajinkyaT%2FDeep_learning_Entity_Embeddings/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ajinkyaT","download_url":"https://codeload.github.com/ajinkyaT/Deep_learning_Entity_Embeddings/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajinkyaT%2FDeep_learning_Entity_Embeddings/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30221193,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-07T14:02:48.375Z","status":"ssl_error","status_checked_at":"2026-03-07T14:02:43.192Z","response_time":53,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep-learning","driving-behavior","entity-embedding","keras-tensorflow"],"created_at":"2024-12-25T08:31:20.884Z","updated_at":"2026-03-07T16:03:20.493Z","avatar_url":"https://github.com/ajinkyaT.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Deep Learning and Entity Embeddings to predict driving behavior and cluster accident hotspots\n\nThis project repo is for Pune Smart City Hackathon organized by Niti Aayog (Planning Commision of India), Government of India\n\nCheck below Jupyter notebooks for solution overview.\n\nData cleaning and processing: [data_processing.ipynb](https://github.com/ajinkyaT/Deep_learning_Entity_Embeddings/blob/master/data_processing.ipynb)\n\nModel architecture: [model_building.ipynb](https://github.com/ajinkyaT/Deep_learning_Entity_Embeddings/blob/master/model_building.ipynb)\n\nVisualizing 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\n\nVisualizing Route-Name Embeddings: [https://plot.ly/~ajinkyaT/5/](https://plot.ly/~ajinkyaT/5/)\n\nVisualizing Stop-Name Embeddings: [https://plot.ly/~ajinkyaT/3/](https://plot.ly/~ajinkyaT/3/)\n\n### Resources\n\n- Guo, C., \u0026 Berkhahn, F. (2016). [Entity embeddings of categorical variables](https://arxiv.org/abs/1604.06737). arXiv preprint arXiv:1604.06737\n- De Brébisson, A., Simon, É., Auvolat, A., Vincent, P., \u0026 Bengio, Y. (2015). [Artificial neural networks\napplied to taxi destination prediction](https://arxiv.org/abs/1508.00021). arXiv preprint arXiv:1508.00021.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fajinkyat%2Fdeep_learning_entity_embeddings","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fajinkyat%2Fdeep_learning_entity_embeddings","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fajinkyat%2Fdeep_learning_entity_embeddings/lists"}