Course Overview
This course presents the steps and considerations for deploying machine learning models in real-world use cases. Students will become skilled at designing machine learning models and analyzing their model's tradeoff between performance and resource usage. They will also read and discuss relevant machine learning systems papers. Topics include creating a good dataset, designing a model, assessing your model's computational/memory/energy needs, when and how to use edge computing, and ways of lowering a model's resource usage.
Masking: You and your classmate's health is a priority in this class. Given the significant caseload of COVID still present in LA county, as well as the risks posed by travel and outside activities, masks will be required in class for the foreseeable future. Please arrive in class with a well-fitting mask on your face (while a surgical, KN95, or N95 mask is preferable, cloth is also fine as long as it actually fits). Though it is permissible to take short sips of water during class to avoid dehydration, you should return your mask to its proper position between sips. Other food or drink must be consumed outside the classroom. If circumstances change, this policy may be revisited later in the semester; in the meantime, if you have concerns, please let me know and I'll be happy to address them.