{"id":9130,"date":"2025-12-16T07:02:26","date_gmt":"2025-12-16T07:02:26","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/12\/16\/the-machine-learning-advent-calendar-day-15-svm-in-excel\/"},"modified":"2025-12-16T07:02:26","modified_gmt":"2025-12-16T07:02:26","slug":"the-machine-learning-advent-calendar-day-15-svm-in-excel","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/12\/16\/the-machine-learning-advent-calendar-day-15-svm-in-excel\/","title":{"rendered":"The Machine Learning \u201cAdvent Calendar\u201d Day 15: SVM in Excel"},"content":{"rendered":"<p>    The Machine Learning \u201cAdvent Calendar\u201d Day 15: SVM in Excel<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>Instead of starting with margins and geometry, this article builds the Support Vector Machine step by step from familiar models. By changing the loss function and reusing regularization, SVM appears naturally as a linear classifier trained by optimization. This perspective unifies logistic regression, SVM, and other linear models into a single, coherent framework.<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/the-machine-learning-advent-calendar-day-15-svm-in-excel\/\">The Machine Learning \u201cAdvent Calendar\u201d Day 15: SVM in Excel<\/a> appeared first on <a href=\"https:\/\/towardsdatascience.com\/\">Towards Data Science<\/a>.<\/p>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    angela shi<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/the-machine-learning-advent-calendar-day-15-svm-in-excel\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Machine Learning \u201cAdvent Calendar\u201d Day 15: SVM in Excel Instead of starting with margins and geometry, this article builds the Support Vector Machine step by step from familiar models. By changing the loss function and reusing regularization, SVM appears naturally as a linear classifier trained by optimization. This perspective unifies logistic regression, SVM, and [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,2076,69,67,245,70,4436],"tags":[199,341,1546],"class_list":["post-9130","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-algorithms","category-artificial-intelligence","category-deep-dives","category-excel","category-machine-learning","category-support-vector-machine","tag-learning","tag-machine","tag-svm"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/9130"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=9130"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/9130\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=9130"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=9130"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=9130"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}