Notebooks and materials for DDL/CEB training.

• Day 1: Visual Data Exploration

  • Intro to matplotlib for visualization (the pyplot API)
  • Data Frames for visual exploration
  • Pandas plotting API
  • Seaborn for visual statistical analysis

• Day 2: Interactive Visualization with Bokeh

  • Interactive analysis
  • Clustering for high dimensional data reduction
  • Visual Analysis: Overview first, zoom and filter, details on demand

• Day 3: Regression Analysis

  • General Linear Models
  • Collinearity
  • Regularization
  • Ridge, Lasso, Elastic Net
  • Regression Evaluation

• Day 4: Classification Models

  • Binary Classification vs. Multi-Class
  • Decision Trees and Random Forrest
  • kNN classification
  • Bayesian Classifiers
  • Logistic Regression
  • SVMs

• Day 5: Visual Diagnostics

  • Evaluating classifiers: F1, Precision, Recall
  • Confusion Matrices and visual confusion matrices
  • ROC/AUC
  • Residuals analysis, Prediction error
  • tSNE and Dimensionality Reduction

• Day 6: Hands-on project that ties everything together