Few-shot learning is a technique in machine learning in which models can learn effectively with just a few training examples. This is particularly useful in situations where large amounts of data are not available or difficult to obtain. Few-shot learning uses transfer learning and meta-learning to transfer knowledge from related tasks and quickly apply it to new problems. This method significantly improves the flexibility and adaptability of AI systems.<\/p>","protected":false},"excerpt":{"rendered":"
Few-Shot Learning ist eine Technik im maschinellen Lernen, bei der Modelle mit nur wenigen Trainingsbeispielen effektiv lernen k\u00f6nnen. Dies ist besonders n\u00fctzlich in Situationen, in denen gro\u00dfe Datenmengen nicht verf\u00fcgbar oder schwer zu beschaffen sind. Few-Shot Learning nutzt Transferlernen und Meta-Lernen, um Wissen aus verwandten Aufgaben zu \u00fcbertragen und schnell auf neue Probleme anzuwenden. Diese […]<\/p>\n","protected":false},"author":1,"featured_media":82,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-86","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-wiki"],"yoast_head":"\n