New York University 4 credits Interactive Media Arts
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.
Our subject experts help with essays, research papers, case studies, discussion posts, and capstone projects for these programs β written from scratch to your course requirements.
Program and course information is reproduced from each university's published academic catalog for informational purposes and may change. Always confirm current requirements with your university. We are an independent academic support service and are not affiliated with or endorsed by the universities listed.
Expert guides on essay writing, citation styles, study skills, and academic success.
View All Articles
Learn how to write a good research question for a paper. Narrow your topic, identify a research problem, and create a focused question with practical examples.
Learn how to choose a research topic you can actually research. Discover how to narrow broad ideas, find reliable sources, and develop a focused research question.
Learn how to cite sources in a research paper using APA, MLA, and Chicago styles, with in-text citation examples and reference-list tips.