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
Training - Data Mining
This three-day-training covers the basic applications and methods of Data Mining. Special focus lies on prediction models.