Introduction to machine learning

Module 5

🟠 … currently under review … 🟠

Lecture Outline

• Introduction to Machine Learning
• Shifting the emphasis on empirical prediction
  • Distinction between supervised & unsupervised algorithms
    • Supervised ML Example
      • Logistic regression
      • 🌳 Random Forest / decision trees 🌲
    • Unsupervised ML Example
      • PCA for dimension reduction
      • K-means Clustering

Lecture slides

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Practice slides

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Practice input data (as subfolder)

Practice R code (as .R file)