What you will learn from this course?
Part I Mathematical Foundations
– Introduction and Motivation
– Linear Algebra
– Analytic Geometry
– Matrix Decompositions
– Vector Calculus
– Probability and Distributions
– Continuous Optimization
Part II Central Machine Learning Problems
– When Models Meet Data
– Linear Regression 289
– Dimensionality Reduction with Principal Component Analysis
– Density Estimation with Gaussian Mixture Models
– Classification with Support Vector Machines
Time to complete : 1 month
Cost : Free
Course Level : Intermediate
Language : English