STA 208: Statistical Machine Learning

Machine learning is how to get computers to automatically learn and improve with experience. Experience comes in the form of data, improvement is with respect to some performance metric, and learning is done by a learning algorithm. There are always computational constraints, such as the architecture, computation time, bandwidth limitations, and so on. So we can more precisely restate the goal thus: to construct learning algorithms that use data to improve with respect to a performance metric and do so under computational constraints.

Due to the COVID-19 lockdown this course has been flipped! You can find the syllabus and download the jupyter notebooks in the Github content page. I am recording my lectures on youtube, which can be found in this playlist. Here is the first video…

STA 220: Data Technologies