IEMS 301: Introduction to Statistical Learning VIEW ALL COURSE TIMES AND SESSIONS Prerequisites A prior course in statistics at the level of IEMS 304; A course in matrix analysis; Proficiency in ...

This course aims at an introduction of some basic aspects in statistical learning and data science. We plan to cover topics in stochastic approximation, pattern recognition, kernel density estimation, ...

This course aims to provide an introduction to the quantitative analysis of data, blending classical statistical methods with recent advances in computational and machine learning.

This course will commence with the classical statistical methodology of linear regression as a foundation. From there, it will progress to provide an introduction to machine learning and data mining ...

Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...

To review advances in knowledge-guided statistical learning methods for analysis of -omics data and spur wider and more frequent applications of such methods in basic, translational, and clinical ...