{"id":20432197,"url":"https://github.com/ikatsov/tensor-house-basic","last_synced_at":"2025-07-11T19:38:05.394Z","repository":{"id":214783120,"uuid":"737285228","full_name":"ikatsov/tensor-house-basic","owner":"ikatsov","description":"A collection of templates for basic enterprise data science and ML tasks","archived":false,"fork":false,"pushed_at":"2023-12-30T17:57:45.000Z","size":6575,"stargazers_count":5,"open_issues_count":0,"forks_count":3,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-06T14:21:55.502Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# TensorHouse Basic Templates\nA collection of templates for basic enterprise data science and ML tasks.\n\n* Generic Regression and Classification Models\n    * Neural Network with Vector Inputs ([notebook](https://github.com/ikatsov/tensor-house-basic/blob/master/regression/vector-models.ipynb))\n    * Neural Network with Sequential Inputs (ConvNet, LSTM, Attention) ([notebook](https://github.com/ikatsov/tensor-house-basic/blob/master/regression/sequence-models.ipynb))\n\n* Enterprise Time Series Analysis\n   * Forecasting Using ARIMA and SARIMA (notebooks\n[1](https://github.com/ikatsov/tensor-house-basic/blob/master/time-series/arima-part-1-algorithm.ipynb)\n[2](https://github.com/ikatsov/tensor-house-basic/blob/master/time-series/arima-part-2-use-case.ipynb))\n   * Decomposition and Forecasting using Bayesian Structural Time Series (BSTS) (notebooks\n[1](https://github.com/ikatsov/tensor-house-basic/blob/master/time-series/bsts-part-1-decomposition.ipynb)\n[2](https://github.com/ikatsov/tensor-house-basic/blob/master/time-series/bsts-part-2-forecasting.ipynb)\n[3](https://github.com/ikatsov/tensor-house-basic/blob/master/time-series/bsts-part-3-forecasting-prophet.ipynb)\n[4](https://github.com/ikatsov/tensor-house-basic/blob/master/time-series/bsts-part-4-forecasting-pymc3.ipynb))\n   * Forecasting and Decomposition using Gradient Boosted Decision Trees (GBDT) ([notebook](https://github.com/ikatsov/tensor-house-basic/blob/master/time-series/gbdt-forecasting.ipynb))\n   * Forecasting and Decomposition using LSTM with Attention ([notebook](https://github.com/ikatsov/tensor-house-basic/blob/master/time-series/lstm-forecasting.ipynb))\n   * Forecasting and Decomposition using VAR/VEC models (notebooks\n[1](https://github.com/ikatsov/tensor-house-basic/blob/master/time-series/var-part-1-forecasting-decomposition.ipynb)\n[2](https://github.com/ikatsov/tensor-house-basic/blob/master/time-series/var-part-2-market-data.ipynb))\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fikatsov%2Ftensor-house-basic","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fikatsov%2Ftensor-house-basic","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fikatsov%2Ftensor-house-basic/lists"}