(my philosophy: teach math using english)

[Teaching Statement]
      Recipient of School of Computer Science's Alan J. Perlis Graduate Student Teaching Award (2015).
      Recipient of Machine Learning Department's Best TA Award (2014).

Teaching Assistantships


Review Videos for Introduction to ML

Here is a set of short remedial videos that are suitable to review pre-requisite material (that one has learnt but forgotten) before an introductory graduate course in machine learning. There are 4 sets of videos - one each on multivariate calculus, multivariate probability/statistics, real/functional analysis and the singular value decomposition. Each set consists of 3 videos, usually around 12-15 minutes long. All videos are hosted on Youtube, and the videos page has a description of prerequisites for the videos and what they cover.
[Reflection on Videos]

Guest Lectures

Outreach


Future Faculty Program

(completed this great multi-year program run by CMU's Eberley Center for Teaching Excellence)
[Transcript]
[Letter]

Related Documents

[Proposed syllabus for UG ML course]
[Proposed (slower) syllabus for 701/702]
[Education Review Committee document]
[Proposed PhD Program Course Policy]
[Proposed Changes to ML Journal Club]