Teaching

Systems & Circuits for Machine Learning

This course studies major topics of hardware for machine learning, including deep learning basics, deep learning framework, digital accelerator design, analog/mixed-signal computation circuit design, emerging technologies for machine learning and so on. The design of the course is structured to provide students a systematic knowledge of hardware design for machine learning, from circuit fundamentals to algorithm optimization. Further, it aims to help students get exposed to state-of-art academic research and gain hands-on experience for industries.

Editing a markdown file for a talk