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xAIM
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  • IDS
  • General
  • Workflows and Exploratory Data Analysis
  • Hierarchical Clustering
  • Explaining Clusters
  • Outlier Detection, Silhouette Score and k-Means Clustering
  • Homework 1
  • Dimensionality Reduction with Principal Components Analysis
  • Data embedding: MDS and t-SNE
  • Homework 2
  • Introduction to Classification, Overfitting, and Evaluation of Predictive Accuracy
  • Classifiers
  • Homework 3
  • Feature Subset Selection
  • Scoring of Classification Models
  • Working with Unstructured Data
  • Homework 4
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Introduction to Data Science

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  6. Images and other files

Images and other files

    • cluster-explain.png
    • DS_Human-Mouse-CD-Maker-Biosciences_CT_DE.pdfDS_Human-Mouse-CD-Maker-Biosciences_CT_DE.pdf
    • hierarchical-clustering.png
    • image-analytics.png
    • k-means.png
    • logo-eu-xaim.png
    • nomogram.png
    • orange-workflow.png
    • pca.png
    • preprocessing.png
    • scoring.png
    • tree.png
    • tsne.png
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