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

6.S191 Team

Nick

Nick Locascio

Lead Organizer

Harini

Harini Suresh

Lead Organizer

Ishaan

Ishaan Gulrajani

Co-Chair

Victoria

Victoria Dean

Co-Chair

Lex

Lex Fridman

Co-Chair

Yo

Yo Shavit

Co-Chair

Ruth

Rue Park

Marketing

Anish

Anish Athalye

TA

Eduardo

Eduardo DeLeon

TA

Jackie

Jackie Xu

TA

Wengong

Wengong Jin

TA

Yala

Adam Yala

TA

Harry

Harry Bleyan

TA

Tianxiao

Tianxiao Shen

TA

Lenail

Alex Lenail

TA

Helen

Helen Zhou

TA

Bowen

Bowen Baker

TA

Prafulla

Prafulla Dhariwal

TA

Alfredo

Alfredo Yanez

TA

Hansa

Hansa Srinivasan

TA

Sponsors

Google Brain


amazon alexa


NVIDIA


IBM Watson