The Machine Learning with R: A Hands-on Introduction workshop at Predictive Analytics World 2020 will use your own computer for the hands-on part. I emailed instructions to all registered participants on Monday, May 18th. If you have not received the email, check your spam folder. If you registered after that date, I’ll send the files as soon as the PAW2020 people send me new registration information. Anyone having problems installing the software should contact me, Bob Muenchen, at muenchen.bob@gmail.com. See you online soon!
Here’s the workshop outline:
- INTRODUCTION
- BASIC CONCEPTS
- TRAINING & TESTING DATA
- RECIPES
- DATA PRE-PROCESSING STEPS
- TREE MODELS (we will cover 5 of these 10 algorithms, chosen via a survey)
- RANDOM FORESTS
- GRADIENT BOOSTING MACHINES
- NEURAL NETWORKS
- K NEAREST NEIGHBORS
- SUPPORT VECTOR MACHINES
- NAIVE BAYES
- LOGISTIC REGRESSION
- DISCRIMINANT ANALYSIS
- LINEAR REGRESSION ANALYSIS
- EVALUATING MODEL EFFECTIVENESS
- CROSS-VALIDATION METHODS
- TUNING GRIDS
- MODEL TUNING
- CLASS IMBALANCE ISSUES
- INTERPRETING BLACK-BOX MODELS
- CHOOSING A MODEL
- CONCLUSION