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Unsupervised Learning in R: K-Means Clustering
/in Data Mining, Data Science, Machine Learning, R Statistics, Statistics, Tutorial/by Markus LangDie Clusteranalyse ist ein gruppenbildendes Verfahren, mit dem Objekte Gruppen – sogenannten Clustern zuordnet werden. Die dem Cluster zugeordneten Objekte sollen möglichst homogen sein, wohingegen die Objekte, die unterschiedlichen Clustern […]
In eigener Sache: Der Data Leader Day 2017
/in Data Science News, Use Cases/by eventsDer Data Science Blog ist Co-Organisator des Data Leader Day 2017 Der Data Leader Day am 09.11.2017 ist ein Event für Unternehmen aus dem deutschsprachigen Raum, das sich mit den Möglichkeiten und Lösungen […]
Artificial Intelligence and Data Science in the Automotive Industry
/in Artificial Intelligence, Big Data, Business Analytics, Business Intelligence, Cloud, Connected Car, Data Science, Machine Learning, Main Category, Manufacturing, Projectmanagement, Use Case, Use Cases/by VolkswagenData science and machine learning are the key technologies when it comes to the processes and products with automatic learning and optimization to be used in the automotive industry of the future. This article defines the terms “data science” (also referred to as “data analytics”) and “machine learning” and how they are related.
Entropie – Und andere Maße für Unreinheit in Daten
/in Artificial Intelligence, Business Analytics, Data Mining, Data Science, Data Science Hack, Machine Learning, Python/by Benjamin AunkoferDieser Artikel ist Teil 1 von 4 der Artikelserie Maschinelles Lernen mit Entscheidungsbaumverfahren. Hierarchische Klassifikationsmodelle, zu denen das Entscheidungsbaumverfahren (Decision Tree) zählt, zerlegen eine Datenmenge iterativ oder rekursiv mit dem […]
What makes a good Data Scientist? Answered by leading Data Officers!
/in Carrier, Education / Certification, Gerneral, Interviews, Main Category/by Benjamin AunkoferWhat makes a good Data Scientist? A question I got asked recently a lot by data science newbies as well as long-established CIOs and my answer ist probably not what […]
Consider Anonymization – Process Mining Rule 3 of 4
/in Audit Analytics, Big Data, Business Analytics, Business Intelligence, Cloud, Data Migration, Data Mining, Data Science, Data Security, Data Warehousing, Main Category, Process Mining/by Anne Rozinat & Christian W. GüntherThis is article no. 3 of the four-part article series Privacy, Security and Ethics in Process Mining. Read this article in German: “Datenschutz, Sicherheit und Ethik beim Process Mining – Regel […]
Interview mit Prof. Dr. Kai Uwe Barthel über Data Science mit Deep Learning
/in Artificial Intelligence, Big Data, Data Mining, Data Science, Deep Learning, Experience, Interview mit CIO, Interviews, Machine Learning, Main Category/by Benjamin AunkoferInterview mit Prof. Dr. Barthel, Chief Visionary Officer der Pixolution GmbH in Berlin, über Funktion, Einsatz und Einstieg in künstliche neuronale Netze. Prof. Kai Barthel ist Gründer und CVO der Pixolution […]
Der Blick für das Wesentliche: Die Merkmalsselektion
/in Big Data, Business Analytics, Data Mining, Data Science, Data Science Hack, Machine Learning, Predictive Analytics, Python, Tool Introduction, Tutorial/by Christoph GreschIn vielen Wissensbasen werden Datensätze durch sehr große Merkmalsräume beschrieben. Während der Generierung einer Wissensbasis wird versucht jedes mögliche Merkmal zu erfassen, um einen Datensatz möglichst genau zu beschreiben. Dabei […]
Responsible Handling of Data – Process Mining Rule 2 of 4
/in Big Data, Business Analytics, Business Intelligence, Data Mining, Data Science, Data Security, Data Warehousing, Process Mining, Projectmanagement/by Anne Rozinat & Christian W. GüntherThis is article no. 2 of the four-part article series Privacy, Security and Ethics in Process Mining. Read this article in German: “Datenschutz, Sicherheit und Ethik beim Process Mining – Regel […]
Five Illusions about Big Data you can’t help but believe in
/in Big Data, Business Analytics, Main Category, Projectmanagement/by Shreya DharBig Data is a smorgasbord of data. Even the marketing world has acknowledged the gravity of Big Data. But alas! Instead of having such a resplendent data power by our […]