{"id":23134397,"url":"https://github.com/danhalligan/islrv2-solutions","last_synced_at":"2025-04-05T07:01:42.789Z","repository":{"id":92111837,"uuid":"550361393","full_name":"danhalligan/ISLRv2-solutions","owner":"danhalligan","description":"Solutions to \"An Introduction to Statistical Learning with Applications in R second edition\"","archived":false,"fork":false,"pushed_at":"2025-01-03T10:41:06.000Z","size":44594,"stargazers_count":124,"open_issues_count":0,"forks_count":33,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-29T06:01:37.742Z","etag":null,"topics":["bookdown","intro-to-statistical-learning","introduction-to-statistical-learning","islr","islr-applied-exercises","islr-book","r","statistical-leaning","statistical-learning"],"latest_commit_sha":null,"homepage":"","language":"CSS","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/danhalligan.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","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":"2022-10-12T16:23:15.000Z","updated_at":"2025-03-23T13:31:13.000Z","dependencies_parsed_at":"2024-08-27T11:59:05.246Z","dependency_job_id":"55341302-e563-4eee-9aaf-18887747ed2b","html_url":"https://github.com/danhalligan/ISLRv2-solutions","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/danhalligan%2FISLRv2-solutions","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danhalligan%2FISLRv2-solutions/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danhalligan%2FISLRv2-solutions/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danhalligan%2FISLRv2-solutions/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/danhalligan","download_url":"https://codeload.github.com/danhalligan/ISLRv2-solutions/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247299828,"owners_count":20916190,"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":["bookdown","intro-to-statistical-learning","introduction-to-statistical-learning","islr","islr-applied-exercises","islr-book","r","statistical-leaning","statistical-learning"],"created_at":"2024-12-17T12:10:19.050Z","updated_at":"2025-04-05T07:01:42.724Z","avatar_url":"https://github.com/danhalligan.png","language":"CSS","funding_links":[],"categories":[],"sub_categories":[],"readme":"# An Introduction to Statistical Learning with Applications in R second edition solutions\n\n[![Build and Deploy](https://github.com/danhalligan/ISLRv2-solutions/actions/workflows/github-actions.yml/badge.svg)](https://github.com/danhalligan/ISLRv2-solutions/actions/workflows/github-actions.yml)\n![License](https://img.shields.io/github/license/danhalligan/ISLRv2-solutions)\n\n![ISLR v2 cover](images/isl_small.png)\n\nThis repository provides my solutions for all exercises in the book\n[\"An Introduction to Statistical Learning with Applications in R\"](https://www.statlearning.com/),\nsecond edition,\nby Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani.\n\nIf you use these solutions or find them useful, please star this repository!\n\n## About these solutions\n\nThe solutions are written in [bookdown] format using (my) \n[ISLRv2 solutions template](https://github.com/danhalligan/ISLRv2-solutions-template).\n\nFor anyone reading this book, I believe there is great value in deriving \nthe solutions yourself, and the template above can be forked to provide a \ngreat starting point as I've created template Rmarkdown files for each chapter\nand transcribed all questions as quotes within the chapter files leaving space\nfor you to write your solutions either as text, or by writing R code chunks.\nFor more details, refer to the template repository.\n\nI've tried my best to provide solutions to each problem in this book, and I\nbelieve my answers should be (at least for the most part) correct. The solutions\nare relatively concise but hopefully comprehensive enough to address the \npurpose of each question.\n\nIf, when reading these solutions, you notice any inconsistencies, mistakes or\nhave any other questions, please feel free to raise an issue or provide \nsuggestions and I'll happily take a look and try to incorporate.\n\n## Compiled solutions\n\nThe HTML book is compiled from the Rmarkdown files in using a [GitHub Actions] \nworkflow and then automatically deployed to [GitHub pages].\n\nYou can view these solutions hosted from GitHub at the following location:\n\n* \u003chttps://danhalligan.github.io/ISLRv2-solutions/\u003e\n\n## Building the solutions\n\nThe R dependencies are provided in the `DESCRIPTION` file and you can install them by running:\n\n```r\ndevtools::install()\n```\n\nOther than that you need the Python packages [tensorflow and keras] installed in the Python environment you are using to run the examples:\n\n```bash\npip3 install tensorflow keras\n```\n\nRebuild the book with compiled solutions by running:\n\n```r\nbookdown::render_book('index.Rmd', 'bookdown::gitbook')\n```\n\nTo render only one file/chapter (e.g. solutions for chapter 2), use:\n\n```r\nrmarkdown::render(input=\"02-statistical-learning.Rmd\", output_format=bookdown::pdf_document2())\n```\n\n[bookdown]: https://github.com/rstudio/bookdown\n[GitHub Actions]: https://docs.github.com/en/actions\n[GitHub pages]: https://pages.github.com/\n[tensorflow and keras]: https://tensorflow.rstudio.com/install/\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdanhalligan%2Fislrv2-solutions","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdanhalligan%2Fislrv2-solutions","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdanhalligan%2Fislrv2-solutions/lists"}