{"id":28797,"date":"2022-10-14T19:19:09","date_gmt":"2022-10-14T17:19:09","guid":{"rendered":"https:\/\/applieditweb.com\/?p=28797"},"modified":"2024-01-31T15:07:34","modified_gmt":"2024-01-31T13:07:34","slug":"data-analytics-das-richtige-tool-fuer-das-richtige-problem","status":"publish","type":"post","link":"https:\/\/applieditweb.com\/de\/data-analytics-das-richtige-tool-fuer-das-richtige-problem\/","title":{"rendered":"Data Analytics: Das richtige Tool f\u00fcr das richtige Problem"},"content":{"rendered":"<p><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-padding-right:240px;--awb-padding-left:248px;--awb-padding-right-medium:0px;--awb-padding-left-medium:0px;--awb-padding-right-small:0px;--awb-padding-left-small:0px;--awb-margin-bottom:40px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1179.36px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-padding-right-medium:10px;--awb-padding-left-medium:10px;--awb-padding-right-small:10px;--awb-padding-left-small:10px;--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:0px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-1\" style=\"--awb-font-size:16px;--awb-line-height:20.16px;--awb-text-color:#d9d9d9;--awb-text-font-family:&quot;Outfit&quot;;--awb-text-font-style:normal;--awb-text-font-weight:400;\"><p><span class=\"lead\">Wir wissen, was Statistiken sind, aber was ist mit maschinellem Lernen? Es ist der Zweig der k\u00fcnstlichen Intelligenz, der versucht, die Natur von Daten durch die automatisierte \u00dcberpr\u00fcfung von Daten f\u00fcr verschiedene Aufgaben zu verstehen, wie z. B.: Wertvorhersagen, Klassifizierung, Clustering&#8230; Normalerweise ist dies so einfach wie das lineare statistische Modell: <span style=\"color: #e32552; font-weight: bold;\">Vorhersage = m \u00b7 Daten + c<\/span>. Und entwickeln Sie einen Algorithmus, der automatisch die Koeffizienten m und c berechnet, wenn sich die Anzahl der Daten \u00e4ndert.<\/span><\/p>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-2 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1179.36px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-1 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-image-element \" style=\"text-align:center;--awb-max-width:640px;--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\" fusion-imageframe imageframe-none imageframe-1 hover-type-none\"><img decoding=\"async\" width=\"1039\" height=\"570\" title=\"data-analysis\" src=\"https:\/\/applieditweb.com\/wp-content\/uploads\/2023\/02\/data-analysis.png\" data-orig-src=\"https:\/\/applieditweb.com\/wp-content\/uploads\/2023\/02\/data-analysis.png\" alt class=\"lazyload img-responsive wp-image-23085\" srcset=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%27http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%27%20width%3D%271039%27%20height%3D%27570%27%20viewBox%3D%270%200%201039%20570%27%3E%3Crect%20width%3D%271039%27%20height%3D%27570%27%20fill-opacity%3D%220%22%2F%3E%3C%2Fsvg%3E\" data-srcset=\"https:\/\/applieditweb.com\/wp-content\/uploads\/2023\/02\/data-analysis-200x110.png 200w, https:\/\/applieditweb.com\/wp-content\/uploads\/2023\/02\/data-analysis-400x219.png 400w, https:\/\/applieditweb.com\/wp-content\/uploads\/2023\/02\/data-analysis-600x329.png 600w, https:\/\/applieditweb.com\/wp-content\/uploads\/2023\/02\/data-analysis-800x439.png 800w, https:\/\/applieditweb.com\/wp-content\/uploads\/2023\/02\/data-analysis.png 1039w\" data-sizes=\"auto\" data-orig-sizes=\"(max-width: 640px) 100vw, 1039px\" \/><\/span><\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-3 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-padding-right:240px;--awb-padding-left:250px;--awb-padding-right-medium:0px;--awb-padding-left-medium:0px;--awb-padding-right-small:0px;--awb-padding-left-small:0px;--awb-margin-top:40px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1179.36px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-2 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-2\" style=\"--awb-font-size:16px;--awb-line-height:20.16px;--awb-text-color:#d9d9d9;--awb-text-font-family:&quot;Outfit&quot;;--awb-text-font-style:normal;--awb-text-font-weight:400;\"><h3 style=\"margin-bottom: 10px;\">Was ist also Deep Learning?<\/h3>\n<p>Es handelt sich um eine Erweiterung des maschinellen Lernens, die darauf abzielt, eine st\u00e4rkere Automatisierung der Datenanalyse und Mustererkennung zu erreichen, indem die Funktionsweise des menschlichen Gehirns nachgeahmt wird (neuronale Netze). Es kann L\u00f6sungen f\u00fcr Modelle anbieten, die herk\u00f6mmliches maschinelles Lernen nicht verstehen kann, auf Kosten einer erheblichen Zunahme der Komplexit\u00e4t und des Ressourcenverbrauchs, die unter anderem die Implementierung in Echtzeit erschweren.<\/p>\n<p>Ist es also besser, maschinelles Lernen oder Deep Learning zu verwenden? Oder sollten wir bei den grundlegenden Statistiken bleiben? Die Antwort ist&#8230; H\u00e4ngt. Alle drei Optionen bieten uns n\u00fctzliche und leistungsstarke Werkzeuge, die hervorragende Ergebnisse liefern. Es liegt am Analysten, zu entscheiden, welches dieser Tools er verwenden m\u00f6chte.<\/p>\n<p>Dank dieser Tools k\u00f6nnen wir die Wahrscheinlichkeit berechnen, dass ein Teil defekt ist. Wir k\u00f6nnen es an jeder Workstation berechnen, an der Daten gesammelt werden, und so vermeiden, dass Ressourcen f\u00fcr ein Teil verschwendet werden, das defekt sein wird.<br \/>\nDurch dieses Know-how haben wir gro\u00dfe Erfolge erzielt, wie z.B. die Reduzierung einer Ausschussquote von 12 %, die Ausschusskosten in Millionenh\u00f6he pro Jahr verursacht, auf eine Ausschussquote von 1,4 %.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":15,"featured_media":23109,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[246],"tags":[],"class_list":["post-28797","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-unkategorisiert"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Data Analytics: Das richtige Tool f\u00fcr das richtige Problem - AppliediT<\/title>\n<meta name=\"description\" content=\"Wir wissen, was Statistik ist, aber was ist mit maschinellem Lernen? 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