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Week 1: Introduction and Optimisation
Week 2: Non-parametric smoothing
Week 3: Regression
Week 4: Classification
Week 5: Support Vector Machines
Week 7: Model Selection part I
Week 8: Model Selection Pert II
Week 9: Clustering Part I
Week 10: Clustering Part II
Week 11: Dimension Reduction
Week 12: Ensembles
Week 13: Final few lectures
Week 6, Term 2: Final Few Lectures
Introduction to Statistical Learning
Optimisation
Kernel Smoothing
Regression
Classification
Model Selection
Clustering
Dimension Reduction
Ensemble Models
Support Vector Machines
Neural Networks
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2024-10521-821 Advanced statistics A / Gevorderde statistiek A - 821
Facilitator:
JUSTIN Harvey
Facilitator:
David Paul Hofmeyr
Facilitator:
Luca Steyn
