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Basic Methods of Data Analysis (2KV)

Lecture Notes:

  • PDF (2014-10-02 / 3MB)

Motivation:

Data analysis and visualization are essential to most fields in science and engineering. The goal of this course is to provide students with a basic tool chest of methods for pre-processing, analyzing, and visualizing scientific data.

Topics:

  • Scatter plots and box plots
  • Basics of classification
  • Basics of regression
  • ANOVA
  • Clustering
  • Principal component analysis (+ visualization, including spectral maps)
  • Singular value decomposition (+ visualization)
  • Matrix factorization (+ visualization)
  • Independent component analysis