{
    "componentChunkName": "component---src-templates-docs-js",
    "path": "/assignments/datasets",
    "result": {"data":{"site":{"siteMetadata":{"title":"Linnaeus University","language":"en"}},"mdx":{"fields":{"id":"dc7e48c1-ce7e-506a-9723-2a62b096b719","title":"Datasets","slug":"/assignments/datasets"},"body":"var _excluded = [\"components\"];\n\nfunction _extends() { _extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\n\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\n\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n\n/* @jsxRuntime classic */\n\n/* @jsx mdx */\nvar _frontmatter = {\n  \"title\": \"Datasets\",\n  \"metaTitle\": \"2DV515 | Datasets\",\n  \"metaDescription\": \"metaDescription\",\n  \"order\": 5\n};\nvar layoutProps = {\n  _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n  var components = _ref.components,\n      props = _objectWithoutProperties(_ref, _excluded);\n\n  return mdx(MDXLayout, _extends({}, layoutProps, props, {\n    components: components,\n    mdxType: \"MDXLayout\"\n  }), mdx(\"p\", null, \"Here you can download the datasets used in the course.\"), mdx(\"table\", null, mdx(\"thead\", {\n    parentName: \"table\"\n  }, mdx(\"tr\", {\n    parentName: \"thead\"\n  }, mdx(\"th\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Dataset\"), mdx(\"th\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Format\"), mdx(\"th\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Description\"), mdx(\"th\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Link\"))), mdx(\"tbody\", {\n    parentName: \"table\"\n  }, mdx(\"tr\", {\n    parentName: \"tbody\"\n  }, mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Wikipedia\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Text\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Larger set of Wikipedia articles (396 about Programming and 245 about Games) to be used for assignment A3\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, mdx(\"a\", {\n    parentName: \"td\",\n    \"href\": \"/courses/web-intelligence-ht25/5cd872d134703b5a21345cd81d1fc72e/wikipedia.zip\"\n  }, \"Download\"))), mdx(\"tr\", {\n    parentName: \"tbody\"\n  }, mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Wikipedia 300\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"ARFF and CSV\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Wikipedia articles (150 about Programming and 150 about Games) to be used for project P3\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, mdx(\"a\", {\n    parentName: \"td\",\n    \"href\": \"/courses/web-intelligence-ht25/c7a89f2949631613b0ae1e3d6c2bf8cb/wikipedia_300.zip\"\n  }, \"Download\"))), mdx(\"tr\", {\n    parentName: \"tbody\"\n  }, mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Wikipedia clustering\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Text\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Wikipedia articles (90 about Programming and 90 about Games) to be used for project P2\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, mdx(\"a\", {\n    parentName: \"td\",\n    \"href\": \"/courses/web-intelligence-ht25/3a5bbd34c9c606715ac20d7255059aac/Wikipedia_clustering.zip\"\n  }, \"Download\"))), mdx(\"tr\", {\n    parentName: \"tbody\"\n  }, mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Blog data\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Text\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"The blog dataset with 99 blogs to be used for assignment A2\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, mdx(\"a\", {\n    parentName: \"td\",\n    \"href\": \"/courses/web-intelligence-ht25/f04f38a14bf729b963678815f79dda5b/blogdata.zip\"\n  }, \"Download\"))), mdx(\"tr\", {\n    parentName: \"tbody\"\n  }, mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Movies example\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"CSV\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"The movie ratings example dataset to be used for assignment A1\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, mdx(\"a\", {\n    parentName: \"td\",\n    \"href\": \"/courses/web-intelligence-ht25/d02d5082a00539619af9878a33285d19/movies_example.zip\"\n  }, \"Download\"))), mdx(\"tr\", {\n    parentName: \"tbody\"\n  }, mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Movies large\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"CSV\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"The larger movie rating dataset to be used for assignment A1\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, mdx(\"a\", {\n    parentName: \"td\",\n    \"href\": \"/courses/web-intelligence-ht25/a4a1e369874cfad255a72c1c0cebf310/movies_large.zip\"\n  }, \"Download\"))), mdx(\"tr\", {\n    parentName: \"tbody\"\n  }, mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"MovieLens 100k\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"CSV\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"The MovieLens 100k ratings dataset to be used for project P1\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, mdx(\"a\", {\n    parentName: \"td\",\n    \"href\": \"/courses/web-intelligence-ht25/70c2b72b6b103639ab1f1ba9b939a0b0/MovieLens_100k.zip\"\n  }, \"Download\"))), mdx(\"tr\", {\n    parentName: \"tbody\"\n  }, mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Iris\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"ARFF and CSV\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Iris dataset to be used for assignment A4\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, mdx(\"a\", {\n    parentName: \"td\",\n    \"href\": \"/courses/web-intelligence-ht25/24af8061a94673da0bfd5c27d7381616/Iris.zip\"\n  }, \"Download\"))), mdx(\"tr\", {\n    parentName: \"tbody\"\n  }, mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Banknote\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"CSV\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, \"Banknote authentication dataset to be used for assignment A4\"), mdx(\"td\", {\n    parentName: \"tr\",\n    \"align\": null\n  }, mdx(\"a\", {\n    parentName: \"td\",\n    \"href\": \"/courses/web-intelligence-ht25/72ef0c270e100726001c3169104941a7/banknote_authentication.zip\"\n  }, \"Download\"))))));\n}\n;\nMDXContent.isMDXComponent = true;","tableOfContents":{},"parent":{"relativePath":"assignments/datasets.md"},"frontmatter":{"metaTitle":"2DV515 | Datasets","metaDescription":"metaDescription"}},"allMdx":{"edges":[{"node":{"fields":{"slug":"/","title":"Web Intelligence (2DV515)"}}},{"node":{"fields":{"slug":"/_playground/_todo-examination","title":"TODO: Examination"}}},{"node":{"fields":{"slug":"/_playground","title":"Playground"}}},{"node":{"fields":{"slug":"/assignments/a1","title":"A1 - Recommendation System"}}},{"node":{"fields":{"slug":"/_playground/expectations","title":"Expectations"}}},{"node":{"fields":{"slug":"/assignments/a2","title":"A2 - Clustering"}}},{"node":{"fields":{"slug":"/assignments/a3","title":"A3 - Search Engine"}}},{"node":{"fields":{"slug":"/assignments/a4","title":"A4 - Machine Learning"}}},{"node":{"fields":{"slug":"/assignments","title":"Assignments"}}},{"node":{"fields":{"slug":"/assignments/datasets","title":"Datasets"}}},{"node":{"fields":{"slug":"/lectures","title":"Lectures"}}},{"node":{"fields":{"slug":"/lectures/lecture01","title":"L01 - Introduction"}}},{"node":{"fields":{"slug":"/lectures/lecture02","title":"L02 - Recommendation Systems"}}},{"node":{"fields":{"slug":"/lectures/lecture03","title":"L03 - Clustering"}}},{"node":{"fields":{"slug":"/lectures/lecture04","title":"L04 - Search Engines"}}},{"node":{"fields":{"slug":"/lectures/lecture05","title":"L05 - What is Machine Learning?"}}},{"node":{"fields":{"slug":"/lectures/lecture07","title":"L07 - Naïve Bayes"}}},{"node":{"fields":{"slug":"/projects","title":"Projects"}}},{"node":{"fields":{"slug":"/projects/p2","title":"P2 – Clustering"}}},{"node":{"fields":{"slug":"/projects/p1","title":"P1 – Recommendation System"}}},{"node":{"fields":{"slug":"/projects/p3","title":"P3 – Text Classification"}}},{"node":{"fields":{"slug":"/projects/p4","title":"P4 – Web scraping"}}},{"node":{"fields":{"slug":"/projects/project","title":"Project"}}},{"node":{"fields":{"slug":"/sandbox/code","title":"Code"}}},{"node":{"fields":{"slug":"/sandbox/basic-elements","title":"Basic elements"}}},{"node":{"fields":{"slug":"/sandbox/exercise","title":"Exercises"}}},{"node":{"fields":{"slug":"/sandbox/frontmatter","title":"Frontmatter"}}},{"node":{"fields":{"slug":"/sandbox/hint","title":"Hint"}}},{"node":{"fields":{"slug":"/sandbox","title":"Sandbox"}}},{"node":{"fields":{"slug":"/sandbox/markdown-import","title":"Imported markdown"}}},{"node":{"fields":{"slug":"/sandbox/mermaid","title":"Mermaid"}}},{"node":{"fields":{"slug":"/lectures/lecture06","title":"L06 - Data and Learning"}}},{"node":{"fields":{"slug":"/sandbox/tabs","title":"Tabs"}}},{"node":{"fields":{"slug":"/sandbox/youtube","title":"YouTube"}}},{"node":{"fields":{"slug":"/study-guide/communication","title":"Communication"}}},{"node":{"fields":{"slug":"/study-guide/deadlines-and-submissions","title":"Deadlines and Submissions"}}},{"node":{"fields":{"slug":"/study-guide/grading","title":"Grading"}}},{"node":{"fields":{"slug":"/study-guide/registration","title":"Registration"}}},{"node":{"fields":{"slug":"/study-guide/welcome","title":"🎉 Welcome"}}},{"node":{"fields":{"slug":"/projects/_DEPRECATED/project","title":"Project"}}},{"node":{"fields":{"slug":"/study-guide/guides/git-and-multiple-computers","title":"Git and multiple computers"}}},{"node":{"fields":{"slug":"/study-guide/guides/an-introduction-to-git","title":"An introduction to Git"}}},{"node":{"fields":{"slug":"/study-guide/guides/git-commit-best-practices","title":"Git commit best practices"}}},{"node":{"fields":{"slug":"/study-guide/guides","title":"Guides"}}},{"node":{"fields":{"slug":"/study-guide/guides/set-up-git","title":"Set up Git"}}},{"node":{"fields":{"slug":"/study-guide/guides/multiple-git-user-configs","title":"Multiple Git user configs"}}},{"node":{"fields":{"slug":"/study-guide/instructors","title":"Instructors"}}},{"node":{"fields":{"slug":"/study-guide/guides/submit-an-assignment-as-a-merge-request","title":"Submit an assignment as a merge request"}}},{"node":{"fields":{"slug":"/study-guide/guides/troubleshooting-ssh","title":"Troubleshooting SSH"}}},{"node":{"fields":{"slug":"/study-guide/guides/this-happens-with-git-commands","title":"This happens with Git commands"}}},{"node":{"fields":{"slug":"/study-guide/readings","title":"Readings"}}},{"node":{"fields":{"slug":"/study-guide","title":"Study Guide"}}}]}},"pageContext":{"id":"dc7e48c1-ce7e-506a-9723-2a62b096b719"}},
    "staticQueryHashes": ["253607798","3706406642","710574383"]}