Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.12202/7315
Title: | COMP3920F: Applied Machine Learning - Fall 2021 |
Authors: | Glassman, Zachary |
Keywords: | Machine Learning |
Issue Date: | Sep-2021 |
Citation: | Glassman, Zachary. (2021, Fall), Syllabus, COMP3920F: Applied Machine Learning, Stern College for Women, Yeshiva University. |
Abstract: | Overview: This course provides an introduction to the practice and theory of machine learning. Upon successful completion of this course you will understand how to apply machine learning to real world problems through proper model and model metric selection. You will also gain experience implementing a real machine learning project leveraging what you have learned in the course. This course covers a wide variety of machine learning topics balancing between theory of machine learning and practical applied skills. The course will involve writing Python code both for labs, home, and exams, however, students are expected to be competent in Python programming through prior programming or independent study. Additionally, students are expected to have a good grasp of |
Description: | SCW syllabus / YU only |
URI: | https://hdl.handle.net/20.500.12202/7315 |
Appears in Collections: | Stern College Syllabi -- Spring and Fall 2021-2022 courses --- COMP (Computers) |
Files in This Item:
File | Description | Size | Format | |
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COMP3920F.Glassman.Fall2021.pdf Restricted Access | 149.63 kB | Adobe PDF | View/Open |
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