{"id":10424,"date":"2026-02-12T07:02:22","date_gmt":"2026-02-12T07:02:22","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2026\/02\/12\/building-an-ai-agent-to-detect-and-handle-anomalies-in-time-series-data\/"},"modified":"2026-02-12T07:02:22","modified_gmt":"2026-02-12T07:02:22","slug":"building-an-ai-agent-to-detect-and-handle-anomalies-in-time-series-data","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2026\/02\/12\/building-an-ai-agent-to-detect-and-handle-anomalies-in-time-series-data\/","title":{"rendered":"Building an AI Agent to Detect and Handle Anomalies in Time-Series Data"},"content":{"rendered":"<p>    Building an AI Agent to Detect and Handle Anomalies in Time-Series Data<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>Combining statistical detection with agentic decision-making<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/building-an-ai-agent-to-detect-and-handle-anomalies-in-time-series-data\/\">Building an AI Agent to Detect and Handle Anomalies in Time-Series Data<\/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    MADHURA RAUT<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/building-an-ai-agent-to-detect-and-handle-anomalies-in-time-series-data\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Building an AI Agent to Detect and Handle Anomalies in Time-Series Data Combining statistical detection with agentic decision-making The post Building an AI Agent to Detect and Handle Anomalies in Time-Series Data appeared first on Towards Data Science. MADHURA RAUT Go to original source<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[678,799,62,3139,83,240,157,2338],"tags":[98,133,84],"class_list":["post-10424","post","type-post","status-publish","format-standard","hentry","category-agentic-ai","category-ai-agent","category-aimldsaimlds","category-anomaly-detection","category-data-science","category-editors-pick","category-python","category-time-series","tag-ai","tag-building","tag-data"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/10424"}],"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=10424"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/10424\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=10424"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=10424"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=10424"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}