Machine Learning for New Interfaces

Catalog description

Machine Learning for New Interfaces is an introductory course with the goal of teaching machine learning concepts in an approachable way to students with basic coding experience and no prior knowledge of machine learning. Students will explore experimental and diverse methods in Machine Learning such as image classification, pose estimation, k-nearest neighbor algorithm and transfer learning. By the end of the course, students will be able to create their own interfaces or applications for the web. They will be able to apply fundamental concepts of Machine Learning, recognize existing Machine Learning models and make Machine Learning projects applicable to everyday life. Prerequisite: INTM-SHU 103 Creative Coding Lab or CSCI-SHU 11 Introduction to Computer Programming Fulfillment: IMA elective; IMB major IMA/IMB elective.