Machine Learning: Deep Learning

Course Description

Deep learning (DL) has emerged as a powerful tool for solving data-intensive learning problems such as supervised learning for classification or regression, dimensionality reduction, and control. As such, it has a broad range of applications including speech and text understanding, computer vision, medical imaging, and perception-based robotics. The goal of this course is to introduce the basic concepts of deep learning (DL). The course will include a brief introduction to the basic theoretical and methodological underpinnings of machine learning, commonly used architectures for DL, DL optimization methods, DL programming systems, and specialized applications to computer vision, speech understanding, and robotics. Students will be expected to solve several DL problems on standardized data sets, and will be given the opportunity to pursue team projects on topics of their choice. Strongly recommended courses: Python, Machine Learning, Statistics, Calc III Prerequisite(s): Students can receive credit for EN.601.482 or EN.601.682, but not both;EN.601.226 AND (AS.110.201 OR AS.110.212 OR EN.553.291 OR EN.553.295) AND (EN.553.211 OR EN.553.310 OR EN.553.311 OR EN.553.420 OR EN.553.421) AND (AS.110.107 OR AS.110.109 OR AS.110.113); Strongly recommended courses: Python, Machine Learning, Statistics, Calc III

Code

EN.601.482

Credits

4

Subject

Computer Science

Programs That Include This Course

• Bachelor's Computer Engineering, Bachelor of Science
• Bachelor's Electrical Engineering, Bachelor of Science
• Bachelor's Systems Engineering, Bachelor of Science
• Doctoral Health Sciences Informatics, PhD
• Minor Computational Medicine, Minor
• Minor Computer Integrated Surgery, Minor