{"id":20676923,"url":"https://github.com/pyro-ppl/pyro-m5-starter-kit","last_synced_at":"2025-04-19T20:57:00.767Z","repository":{"id":99161209,"uuid":"246208127","full_name":"pyro-ppl/Pyro-M5-Starter-Kit","owner":"pyro-ppl","description":"Learn Pyro through the M5 forecasting competition","archived":false,"fork":false,"pushed_at":"2020-04-07T04:38:17.000Z","size":6810,"stargazers_count":83,"open_issues_count":1,"forks_count":10,"subscribers_count":7,"default_branch":"master","last_synced_at":"2024-07-31T21:55:18.057Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pyro-ppl.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":"2020-03-10T04:28:18.000Z","updated_at":"2024-06-21T03:30:59.000Z","dependencies_parsed_at":"2023-06-04T08:15:25.428Z","dependency_job_id":null,"html_url":"https://github.com/pyro-ppl/Pyro-M5-Starter-Kit","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pyro-ppl%2FPyro-M5-Starter-Kit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pyro-ppl%2FPyro-M5-Starter-Kit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pyro-ppl%2FPyro-M5-Starter-Kit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pyro-ppl%2FPyro-M5-Starter-Kit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pyro-ppl","download_url":"https://codeload.github.com/pyro-ppl/Pyro-M5-Starter-Kit/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249799916,"owners_count":21326995,"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":"2024-11-16T21:14:00.708Z","updated_at":"2025-04-19T20:57:00.739Z","avatar_url":"https://github.com/pyro-ppl.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Pyro M5 Starter Kit\n\nThis repo aims to help you learn the [Pyro](https://pyro.ai) probabilistic programming language through the [M5 forecasting competition](https://www.kaggle.com/c/m5-forecasting-uncertainty/overview).\n\n## Documentation resources\n\n- Pyro [reference docs](https://docs.pyro.ai)\n  - [Installation](https://docs.pyro.ai/en/stable/installation.html)\n  - [Forecasting](https://docs.pyro.ai/en/stable/contrib.forecast.html)\n  - [Distributions](https://docs.pyro.ai/en/stable/distributions.html)\n  - [Reparameterizers](https://docs.pyro.ai/en/stable/infer.reparam.html)\n  - [Time series](https://docs.pyro.ai/en/stable/contrib.timeseries.html)\n- Pyro [tutorials](https://pyro.ai/examples)\n- Pyro [forum](https://forum.pyro.ai)  \u003c---- ask questions here\n- PyTorch [reference docs](https://pytorch.org/docs/stable/index.html)\n- M5 competition [overview](https://www.kaggle.com/c/m5-forecasting-uncertainty/overview)\n- M5 exploratory data analysis [notebook](https://www.kaggle.com/headsortails/back-to-predict-the-future-interactive-m5-eda) (thanks to Martin Henze)\n\nI'd recommend starting with the following sequence of Pyro tutorials. These build up to [Forecasting III's Model2](https://pyro.ai/examples/forecasting_iii.html#Deeper-hierarchical-models) which is very close to the M5 forecasting problem.\n\n1. [Pyro models](https://pyro.ai/examples/intro_part_i.html) *recommended*\n2. [Pyro inference](https://pyro.ai/examples/intro_part_ii.html)\n3. [Stochastic variational inference I](https://pyro.ai/examples/svi_part_i.html)\n4. [Stochastic variational inference II](https://pyro.ai/examples/svi_part_ii.html) *recommended*\n5. [Stochastic variational inference III](https://pyro.ai/examples/svi_part_iii.html)\n6. [Tensor Shapes](https://pyro.ai/examples/tensor_shapes.html) *recommended*\n7. [Forecasting I: univariate, heavy tailed](https://pyro.ai/examples/forecasting_i.html) *recommended*\n8. [Forecasting II: state space models](https://pyro.ai/examples/forecasting_i.html)\n9. [Forecasting III: hierarchical models](https://pyro.ai/examples/forecasting_i.html) *recommended*\n\n## Contributions welcome!\n\nWe believe in friendly competition that builds on collaboration.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpyro-ppl%2Fpyro-m5-starter-kit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpyro-ppl%2Fpyro-m5-starter-kit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpyro-ppl%2Fpyro-m5-starter-kit/lists"}