Schedule
Supplemental Resources
Each of the below links to the full book. Icons in the schedule link to specific chapters. All books except two are freely available from the provided links. Applied Predictive Modeling is available online through UO Libraries. Mathematics for Machine Learning is not necessary for this course; however, I provide the link in case anybody is interested. A shorter version of similar content is freely available.
Mathematics for Machine Learning
Mathematics for Machine Learning (short)
Quantifying the Quality of Predictions
Hands-On Machine Learning with R
An Introduction to Statistical Learning
The Elements of Statistical Learning
Feature Engineering and Selection
Applied Predictive Modeling***
*** PDF is available through UO Libraries
Mathematics for Machine Learning (short)
Quantifying the Quality of Predictions
Hands-On Machine Learning with R
An Introduction to Statistical Learning
The Elements of Statistical Learning
Feature Engineering and Selection
Applied Predictive Modeling***
*** PDF is available through UO Libraries
Week 0 - precourse
Topics
Slides
Notes
Assigned
Due
Supplemental Reading
NA
Warm-up I: Linear Algebra
A brief overview of some linear algebra concepts will be introduced using R to develop some terminology.
NA
Warm-up II: Optimization
A brief overview of some calculus and optimization will be introduced using R.
Week 1
Topics
Slides
Notes
Assigned
Due
Supplemental Reading
Week 2
Topics
Slides
Notes
Assigned
Due
Supplemental Reading