Machine learning (ML) is a collection of mathematical methods for pattern recognition. These methods identify patterns, for example, by breaking down datasets into hierarchical structures that minimize entropy. Alternatively, similarities between datasets are determined using vectors, and trained or untrained patterns are derived from them. Machine learning algorithms are indeed capable of solving many everyday or even highly specialized problems. In the practical work of a machine learning developer, however, problems frequently arise when either too little data is available or the data has too many dimensions. Entropy-driven learning algorithms such as decision trees become too complex when there are many dimensions and vectors. <\/p>","protected":false},"excerpt":{"rendered":"
Maschinelles Lernen, Machine Learning (ML), ist eine \u00e4ltere Computerwissenschaft, die Aspekte der Bilderkennung, …<\/p>","protected":false},"author":3,"featured_media":10771,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[3],"tags":[30,31,32],"class_list":["post-10770","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-facts","tag-computerwissenschaft","tag-machine-learning","tag-ml"],"acf":[],"yoast_head":"\n