Prediction: Machine Learning and Statistics | Sloan School of Management | MIT OpenCourseWare

Course Info

Instructor

Prof. Cynthia Rudin

Departments

Sloan School of Management

As Taught In

Spring 2012

Level

Graduate

Topics

Learning Resource Types

Lecture Notes

Projects with Examples

Instructor Insights

Download Course

Lecture Notes

15.097 Lecture 1: Rule mining and the Apriori algorithm

15.097 Lecture 10: Boosting

15.097 Lecture 11: Convex optimization

15.097 Lecture 12: Support vector machines

15.097 Lecture 13: Kernels

15.097 Lecture 14: Statistical learning theory

15.097 Lecture 15: Bayesian analysis

15.097 Lecture 2: R for machine learning

15.097 Lecture 3: Fundamentals of learning

15.097 Lecture 4: Inference

15.097 Lecture 5: Clustering

15.097 Lecture 6: k-nearest neighbors

15.097 Lecture 7: Naïve Bayes

15.097 Lecture 8: Decision trees

15.097 Lecture 9: Logistic regression

Course Info

Instructor

Prof. Cynthia Rudin

Departments

Sloan School of Management

As Taught In

Spring 2012

Level

Graduate

Topics

Learning Resource Types

Lecture Notes

Projects with Examples

Instructor Insights

Download Course

MIT Open Learning

Over 2,500 courses & materials

Freely sharing knowledge with learners and educators around the world. Learn more

© 2001–2026 Massachusetts Institute of Technology

Accessibility

Creative Commons License

Terms and Conditions

Proud member of:

© 2001–2026 Massachusetts Institute of Technology