Course Description
A week-long intro to deep learning methods with applications to machine translation, image recognition, game playing, image generation and more. A collaborative course incorporating labs in TensorFlow and peer brainstorming along with lectures. Course concludes with project proposals with feedback from staff and panel of industry sponsors.
Recommended Pre-Req: one of 6.036, 6.034, 6.008, 6.867, 6.864, 6.804, 15.075, IDS.301, 6.047, 6.041, 6.438 or equivalent experience
Time and Location
Jan 30 - Feb 3
10:30am-1:30pm, Room 34-100
10:30a-11:15pm: Lecture Part 1
11:15a-12:00pm: Lecture Part 2
12:00pm-12:30pm: Coffee Break
12:30pm-1:30pm: Lab (Hands-On TensorFlow Tutorials)
Grading Policy
P/F based on completion of project proposal assignment
Project Proposals
Project proposals will be 1-minute pitches of a novel deep learning algorithm, application, open-source contribution, plan to create an interesting dataset, or other contributions. Sponsors will judge and select top projects as award winners. Alternative to project proposal is to submit a 1-page review of an interesting deep learning paper.
Questions?
Reach out to introtodeeplearning-staff@mit.edu
Nick Locascio
Lead Organizer
Harini Suresh
Lead Organizer
Ishaan Gulrajani
Co-Chair