This is a course in how to utilize data: infer,
predict, coerce, and classify. We will cover a large
breadth of material, spanning supervised and unsupervised
learning, recommender systems, and
Bayesian modelling, to a high level of mathematical
rigor. Upon successful completion of the course, students
should be fully equipped to enter industry as a data
scientist, read active research in the field of Machine
Learning, and approach huge (data and otherwise) problems
seen in the real world.
Additionally, another goal of this course is to become comfortable using Amazon Web Services and GitHub as these tools are extremely prevalent in industry and academia when developing and deploying models. To that end, all code for homework and your final project will be hosted on GitHub.