Courses

Courses taught at Tufts University:

Foundational courses

• CS 136: Statistical Pattern Recognition
  • Introduce students to probabilistic modeling of data (maximum likelihood, Bayesian conjugacy, etc.)
  • Typical enrollment: 30 students / semester
  • 2024 Spring
  • 2023 Spring
  • 2021 Spring
  • 2020 Spring

• CS 135: Introduction to Machine Learning
  • Introduce students to supervised learning (linear/logistic regression, neural nets, trees)
  • Typical enrollment: 100 students / semester
  • 2023 Fall
  • 2020 Fall
  • 2019 Spring

Advanced courses that prepare students for research

• CS 152-L3D: Learning from Limited Labeled Data
  • Transfer learning, self-supervised learning, semi-supervised learning, etc.
  • 2024 Fall

• CS 152-BDL: Bayesian Deep Learning
  • Using Bayesian ideas to improve robustness of deep neural nets
  • 2022 Fall
  • 2019 Fall
  • 2018 Fall

Distant Past

Courses TA'd at Brown University while a graduate student:

• Fall 2013: CS 142 Introduction to Machine Learning
  • Internet archive link (since Brown might have taken down the old course website): https://web.archive.org/web/20170606205059/http://cs.brown.edu/courses/cs142/fall2013/