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Training - Data Mining
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With growing amounts of data we need new methods for data analysis. This three-day-class gives an overview over the most important datamining-methods. Unsupervised learning methods try to find structures in your data without an explicit response variable. Typical unsupervised methods are principal component- and cluster-analysis. The main topic in this class are prediction models. This includes logistic regression, decision trees and neural networks. The class concludes with the general idea of ensemble-prediction-models.

Content:
  • Uses cases in data mining
  • Clustering (KMEANS, Hierarchical clustering)
  • Principal component analysis (PCA)
  • Prediction modeling (logistic regression, decision trees, neural networks)
  • Concept of ensemble-models

Requirements:

None

Duration of the training: 3 days