Week 1: Machine learning and vector calculus

DATA 442/642 · Week 1

Module 1 — Machine learning and vector calculus

Notes

• 1.1 Machine Learning Basics(slides)
• 1.2 Why Vector Calculus(slides)
• 1.3 Derivatives for Optimization(slides)
• 1.4 Basic Vector Calculus(slides)

Labs

• Lab 1: A 5-Detector on MNIST(PDF)

Additional

• 1. ML math basics(PDF)
• OLS variance and residuals(PDF)
• Loss functions(PDF)
• Loss functions (course notes)(PDF)
• Bias(PDF)

Discussion

• Name one supervised and one unsupervised method this course will treat later, and what label each one does or does not see.
• Why is the normal equation a calculus problem, not a programming problem?