{"id":11611,"date":"2016-02-09T13:40:00","date_gmt":"2016-02-09T05:40:00","guid":{"rendered":"https:\/\/ihower.tw\/blog\/?p=11611"},"modified":"2023-06-12T20:34:44","modified_gmt":"2023-06-12T12:34:44","slug":"coursera-%e6%a9%9f%e5%99%a8%e5%ad%b8%e7%bf%92-%e4%b8%8a%e8%aa%b2%e5%bf%83%e5%be%97","status":"publish","type":"post","link":"https:\/\/ihower.tw\/blog\/11611-coursera-%e6%a9%9f%e5%99%a8%e5%ad%b8%e7%bf%92-%e4%b8%8a%e8%aa%b2%e5%bf%83%e5%be%97","title":{"rendered":"Coursera: \u53f0\u5927\u8cc7\u5de5 Machine Learning \u4e0a\u8ab2\u5fc3\u5f97"},"content":{"rendered":"\n

\u6574\u7406\u8a18\u9304\u4e00\u4e0b\u5728 Coursera \u4fee\u53f0\u5927\u8cc7\u5de5\u6797\u8ed2\u7530\u8001\u5e2b\u7684\u6a5f\u5668\u5b78\u7fd2\u8ab2\u7a0b<\/a>\u5fc3\u5f97\uff0c\u5206\u6210\u5169\u9580\u8ab2\u4e0a\u4e0b\u5169\u500b\u5b78\u671f\u3002<\/p>\n\n\n\n

2016\u5e742\u67089\u65e5 21:12 UTC+08<\/p>\n\n\n\n

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\u62ff\u5230\u53f0\u5927\u6a5f\u5668\u5b78\u7fd2\u6280\u6cd5\u7684\u8b49\u66f8\u5566 t.co\/AwlAdFgkj0<\/a> #coursera # \u52aa\u529b\u4e86\u534a\u5e74\u7d42\u65bc\u89e3\u958b Machine Learning \u7684\u6210\u5c31\uff0c\u5728\u6280\u6cd5\u8ab2\u4e2d\u5be6\u4f5c\u4e86 SVM\u3001AdaBoost\u3001Decision Tree \u548c NNet \u6f14\u7b97\u6cd5\u3002<\/p>\n\n\n\n

2015\u5e7412\u670828\u65e5 21:33 UTC+08<\/p>\n\n\n\n

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\u63a5\u9023\u5169\u500b\u6a5f\u5668\u5b78\u7fd2\u4f5c\u696d\u5be6\u4f5c\u51fa AdaBoost \u548c Decision Tree(CART) \u53ca Random forest (\u6211\u7528Ruby\u5beb)\uff0c\u8ddf\u5176\u4ed6\u6a21\u578b\u76f8\u6bd4\uff0c\u96e3\u5f97\u4e0d\u9700\u8981\u592a\u591a\u6578\u5b78\uff0c\u611f\u89ba\u7c21\u55ae\u591a\u4e86 XD \u53e6\u5916\u767c\u73fe Python scikit-learn \u7684 Decision Tree \u4e5f\u662f\u7528 CART \u6f14\u7b97\u6cd5\uff0c\u6240\u4ee5\u4e5f\u62ff\u4f86\u6e2c\u4e86\u4e00\u4e0b\u81ea\u5df1\u5beb\u7684\u5c0d\u4e0d\u5c0d\uff0c\u5b83\u9084\u53ef\u4ee5\u628a\u6c7a\u7b56\u6a39\u532f\u51fa Graphviz \u5716\u771f\u662f\u592a\u68d2\u4e86\u3002 \u63a5\u4e0b\u4f86\u8981\u9032\u5165\u985e\u795e\u7d93\u7db2\u8def\u4e86\u3002<\/p>\n\n\n\n

2015\u5e7411\u670811\u65e5 0:02 UTC+08<\/p>\n\n\n\n

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\u4ea4\u4e86 Coursera \u53f0\u5927\u6a5f\u5668\u5b78\u7fd2\u57fa\u77f3\u6700\u5f8c\u4e00\u6b21\u4f5c\u696d\uff0c\u6536\u7a6b\u9817\u8c50\uff0c\u6bcf\u6b21\u4f5c\u696d\u90fd\u5beb\u597d\u4e45\u3002\u9019\u5802\u8ab2\u6bd4\u8f03\u504f\u7406\u8ad6\uff0c\u4e0a\u5230\u7b2c\u4e8c\u6b21\u4f5c\u696d\u6700\u7406\u8ad6\u7684\u6642\u5019\uff0c\u5dee\u9ede\u5c31\u8981\u653e\u68c4\u4e86\uff0c\u597d\u96aa\u6490\u4e86\u4e0b\u4f86\u5f8c\u9762\u8b1b overfitting \u7684\u90e8\u5206\u6211\u8a8d\u70ba\u662f\u9019\u5802\u8ab2\u6700\u7cbe\u5f69\u7684\u90e8\u5206\u3002\u70ba\u4ec0\u9ebc\u505a feature transform \u548c regularation\uff0c\u5982\u4f55\u7528 validation \u7b49\u7b49\uff0c\u7406\u8ad6\u8cab\u7a7f\u524d\u5f8c\u3002\u9019\u4e9b\u5176\u5be6\u4e4b\u524d\u5728\u4fee edX Spark ML \u8ab2\u7684\u6642\u5019\uff0c\u4e5f\u6709\u7167\u8457\u7528\u9019\u4e9b\u6280\u5de7\uff0c\u4f46\u662f\u90fd\u4e0d\u77e5\u9053\u70ba\u4ec0\u9ebc\uff0c\u73fe\u5728\u77e5\u9053\u7406\u8ad6\u4e4b\u5f8c\u8d85\u6709\u611f\u89ba\u3002 \u63a5\u8457\u5c31\u662f\u6a5f\u5668\u5b78\u7fd2\u6280\u6cd5\u4e86\uff0c\u611f\u89ba\u53c8\u662f\u4e00\u6574\u500b\u8d85\u96e3\uff0cSVM \u6211\u4f86\u4e86!<\/p>\n","protected":false},"excerpt":{"rendered":"

\u6574\u7406\u8a18\u9304\u4e00\u4e0b\u5728 Coursera \u4fee\u53f0\u5927\u8cc7\u5de5\u6797\u8ed2\u7530\u8001\u5e2b\u7684\u6a5f\u5668\u5b78\u7fd2\u8ab2\u7a0b\u5fc3\u5f97\uff0c\u5206\u6210\u5169\u9580\u8ab2\u4e0a\u4e0b\u5169\u500b\u5b78\u671f\u3002 2016\u5e74 … <\/p>\n

\u95b1\u8b80\u5168\u6587\u3008Coursera: \u53f0\u5927\u8cc7\u5de5 Machine Learning \u4e0a\u8ab2\u5fc3\u5f97\u3009<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[74],"tags":[],"class_list":["post-11611","post","type-post","status-publish","format-standard","hentry","category-data-science","entry"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p1q6tG-31h","jetpack_sharing_enabled":true,"jetpack_likes_enabled":true,"_links":{"self":[{"href":"https:\/\/ihower.tw\/blog\/wp-json\/wp\/v2\/posts\/11611","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ihower.tw\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ihower.tw\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ihower.tw\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ihower.tw\/blog\/wp-json\/wp\/v2\/comments?post=11611"}],"version-history":[{"count":8,"href":"https:\/\/ihower.tw\/blog\/wp-json\/wp\/v2\/posts\/11611\/revisions"}],"predecessor-version":[{"id":11626,"href":"https:\/\/ihower.tw\/blog\/wp-json\/wp\/v2\/posts\/11611\/revisions\/11626"}],"wp:attachment":[{"href":"https:\/\/ihower.tw\/blog\/wp-json\/wp\/v2\/media?parent=11611"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ihower.tw\/blog\/wp-json\/wp\/v2\/categories?post=11611"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ihower.tw\/blog\/wp-json\/wp\/v2\/tags?post=11611"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}