MIT Deep Learning and Artificial Intelligence Lectures

This page is a collection of lectures on deep learning, deep reinforcement learning, autonomous vehicles, and AI given at MIT in 2017 through 2020. Stay tuned for 2021.

Deep Learning - 2020

Complete Statistical Theory of Learning
Vladimir Vapnik
Columbia University
Efficient Computing for Deep Learning
Vivienne Sze
MIT
Privacy Preserving AI
Andrew Trask
OpenMined, University of Oxford
Deep Learning State of the Art (2020)
Lex Fridman
MIT

Deep Learning - 2019

Introduction to Deep RL
Lex Fridman
MIT
Deep Learning State of the Art (2019)
Lex Fridman
MIT
Deep Learning Basics
Lex Fridman
MIT

Deep Learning - 2018

Deep Learning for Human Sensing
Lex Fridman
MIT
Computer Vision
Lex Fridman
MIT
Deep Reinforcement Learning
Lex Fridman
MIIT, Deep Reinforcement Learning
Deep Learning
Lex Fridman
MIT

Deep Learning - 2017

Deep Learning for Human-Sensing
Lex Fridman
MIT
Recurrent Neural Networks
Lex Fridman
MIT
Convolutional Neural Networks
Lex Fridman
MIT
Deep Reinforcement Learning
Lex Fridman
MIT
Deep Learning for Self-Driving Cars
Lex Fridman
MIT

Self Driving Cars

Motion Planning
Sertac Karaman
Professor, MIT
Technology, Policy & Safety
Chris Gerdes
Professor, Stanford
Aurora
Sterling Anderson
Co-Founder, Aurora
nuTonomy
Emilio Frazzoli
CTO, nuTonomy
Waymo
Sacha Arnoud
Director of Engineering, Waymo
Self-Driving Cars (2018)
Lex Fridman
Research Scholar, MIT
Aptiv Autonomous Mobility
Karl Iagnemma
President, Aptiv Autonomous Mobility
Voyage
Oliver Cameron
CEO, Voyage
Waymo (2019)
Drago Anguelov
Principal Scientist, Waymo
Self-Driving Cars State of the Art (2019)
Lex Fridman
Self Driving, MIT
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