CSCI2470
Deep Learning
Fall 2024
Deep Learning belongs to a broader family of machine learning methods. It is a particular version of artificial neural networks that emphasizes learning representation with multiple layers of networks. Deep Learning, plus the specialized techniques that it has inspired (e.g. convolutional neural networks, recurrent neural networks, and transformers), have led to rapid improvements in many applications, such as computer vision, machine learning, sound understanding, and robotics. This course gives students an overview of the prominent techniques of Deep Learning and its applications in computer vision, language understanding, and other areas. It also provides hands-on practice of implementing deep learning algorithms in Python. A final project will implement an advanced piece of work in one of these areas. Students may take CSCI 2470 or CSCI 1470 but not both.
Instructor(s): | |
Meets: | TTh 1pm-2:20pm in CIT Center (Thomas Watson CIT) 165 |
Exam: | No final exam has been scheduled for this course by the department through the registrar's office. Please consult syllabus or contact instructor. If an exam were to have scheduled, it would have been held: |
Max Seats: | 60 |
CRN: | 18910 |