– Classification, regression, and conditional probability estimation
– Generative and discriminative models
– Linear models and extensions to nonlinearity using kernel methods – Ensemble methods: boosting, bagging, random forests
– Representation learning: clustering, dimensionality reduction, autoencoders, deep nets

Build your subject-matter expertise.
This course is part of the Machine Learning Specialization When you enroll in this course, you’ll also be enrolled in this Specialization. Learn new concepts from industry experts Gain a foundational understanding of a subject or tool Develop job-relevant skills with hands-on projects