ML, AI, and R: from Algo to Deployment
  1. Setup
  • Setup
  • Preprocessing
    • Data Preprocessing for ML / AI
    • content/course/Modules/10-Preprocessing/eda.qmd
    • content/course/Modules/10-Preprocessing/missingdata.qmd
    • content/course/Modules/10-Preprocessing/outliers.qmd
    • content/course/Modules/10-Preprocessing/scaling.qmd
    • content/course/Modules/10-Preprocessing/dimensional
  • Sampling
  • Recipes
  • Models
    • Linear Regression with tidymodels
    • Logistic Regression
    • Random Forests for Classification
    • Boosting
    • Support Vector Machines
    • K-means Clustering
    • Ensembles as Emergent Systems: From Simple Trees to Collective Intelligence
  • Workflow
  • Model Tuning
  • Model Evaluation
  • Neural Nets and DL
  • Model Deployment

Setting up for Tidy Models

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Data Preprocessing for ML / AI

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