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Courses I've taught over the years. Click on the entries to see more details and materials!

From Theory to Practice: Deep Learning for NLP

A 5-day lecture series covering the basics of machine learning, neural networks and deep neural networks. We look at several deep neural network architectures from the perspective of applying them to various classification tasks, such as sequence prediction and generation. Every lecture is accompanied with practice problems implemented in Keras, a popular Python framework for deep learning.

Deep Learning for Machine Translation

A 10-lecture crash course in deep learning, specialized towards machine translation. These lectures cover Language Modeling, basics of Machine Learning, Neural Networks, Recurrent Neural Networks and finish with Sequence to Sequence models for Machine translation. We take a look at practical considerations, along with exercises to help solidify the concepts.

15-213: Introduction to Computer Systems

Teaching Assistant
As a Teaching Assistant for the Introduction to Computer Systems course at CMU-Q, I prepared and delivered recitation sections weekly over the 14-week semester. These materials include the slides, code and illustrations that hopefully make Computer Systems more accessible!