{"id":24578409,"url":"https://github.com/elemento24/feature-engineering-time-series-forecasting","last_synced_at":"2025-03-17T14:25:15.252Z","repository":{"id":188838979,"uuid":"678482054","full_name":"Elemento24/Feature-Engineering-Time-Series-Forecasting","owner":"Elemento24","description":"This repo consists of all the Projects \u0026 Resources from Soledad and Kishan's course, Feature Engineering for Time Series Forecasting","archived":false,"fork":false,"pushed_at":"2023-08-17T03:30:35.000Z","size":3354,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-01-23T23:59:08.920Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Elemento24.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2023-08-14T16:45:54.000Z","updated_at":"2023-08-14T16:46:08.000Z","dependencies_parsed_at":"2023-08-17T04:59:30.230Z","dependency_job_id":null,"html_url":"https://github.com/Elemento24/Feature-Engineering-Time-Series-Forecasting","commit_stats":null,"previous_names":["elemento24/feature-engineering-time-series-forecasting"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Elemento24%2FFeature-Engineering-Time-Series-Forecasting","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Elemento24%2FFeature-Engineering-Time-Series-Forecasting/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Elemento24%2FFeature-Engineering-Time-Series-Forecasting/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Elemento24%2FFeature-Engineering-Time-Series-Forecasting/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Elemento24","download_url":"https://codeload.github.com/Elemento24/Feature-Engineering-Time-Series-Forecasting/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244048156,"owners_count":20389288,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":[],"created_at":"2025-01-23T23:59:20.466Z","updated_at":"2025-03-17T14:25:15.233Z","avatar_url":"https://github.com/Elemento24.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Feature Engineering for Time Series Forecasting - Code Repository\n\n[\u003cimg src=\"images/FETSF_banner.png\" width=\"1500\"\u003e](https://www.trainindata.com/p/feature-engineering-for-forecasting)\n\n\n![PythonVersion](https://img.shields.io/badge/python-3.8%20%7C%203.9%20%7C%203.10-success)\n[![License https://github.com/trainindata/feature-engineering-for-time-series-forecasting/blob/master/LICENSE](https://img.shields.io/badge/license-BSD-success.svg)](https://github.com/trainindata/feature-engineering-for-time-series-forecasting/blob/master/LICENSE)\n[![Sponsorship https://www.trainindata.com/](https://img.shields.io/badge/Powered%20By-TrainInData-orange.svg)](https://www.trainindata.com/)\n\nPublished October, 2022\n\nActively maintained.\n\n## Links\n\n- [Online Course](https://www.trainindata.com/p/feature-engineering-for-forecasting)\n\n\n## Table of Contents\n\n1. **Tabularizing time series data**\n\t1. Features from the target\n\t2. Features from exogenous variables\n\t3. Single step forecasting\n\n2. **Challenges in feature engineering for time series**\n\t1. Train-test split\n\t2. Pipelines\n\t3. Multistep forecasting\n\t4. Direct forecasting\n\t5. Recursive forecasting\n\t\n3. **Time series decomposition**\n\t1. Components of a time series: trend and seasonality\n\t2. Multiplicative and additive models\n\t3. Log transform and Box-Cox\n\t4. Moving averages\n\t5. LOWESS, STL, and multiseasonal time series decomposition\n\n4. **Missing data imputation**\n\t1. Forward and backward filling\n\t2. Linear and spline interpolation\n\t3. Seasonal decomposition and interpolation\n\n5. **Outliers**\n\t1. Rolling statistics for outlier detection\n\t2. LOWESS for outlier detection\n\t3. STL for outlier detection\n\n6. **Lag features**\n\t1. Autoregressive processes\n\t2. Lag plots\n\t3. ACF, PACF, CCF\n\t4. Seasonal lags\n\t4. Creating lags with open-source\n\n7. **Window features**\n\t1. Rolling windows\n\t2. Expanding windows\n\t3. Exponentially weighted windows\n\t4. Creating window features with open-source\n\n8. **Trend features**\n\t1. Using time to model linear trend\n    2. Polynomial features of time to model non-linear trend\n\t3. Changepoints \u0026 piecweise linear trends to model non-linear trend\n\t4. Forecasting time series with trend using tree-based models\n\t5. Creating trend features with open-source\n\n9. **Seasonality features**\n\t1. Seasonal lags\n\t2. Seasonal dummies\n\t3. Seasonal decomposition methods\n\t4. Fourier terms\n\t5. Creating seasonality features with open-source\n\n10. **Datetime features**\n\t1. Extracting features from date and time\n\t2. Periodic features\n\t3. Calendar events\n\t4. Creating datetime features with open-source\n\n11. **Categorical Features**\n\t1. One hot encoding\n\t2. Target encoding\n\t3. Rolling entropy and rolling majority\n\n\n- [Online Course](https://www.trainindata.com/p/feature-engineering-for-forecasting)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Felemento24%2Ffeature-engineering-time-series-forecasting","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Felemento24%2Ffeature-engineering-time-series-forecasting","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Felemento24%2Ffeature-engineering-time-series-forecasting/lists"}