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1:25:16ENFrom Hand-Built Features to ResNets: Andrej Karpathy's Crash Course in Convolutional NetworksModeration: Lex FridmanA 2016 Deep Learning School talk covering how convnets work, how the ImageNet winners evolved, and how to apply them without being a hero.
1:11:50ENData Is Everything: Teaching Self-Driving Cars to Understand the Human Behind the WheelModeration: Lex FridmanIn an MIT lecture, Lex Fridman shows how deep learning can sense pedestrians, driver posture, gaze, emotion and cognitive load, and why that matters for human-centered autonomy.
1:19:52ENFrom Pixels to Steering Wheels: Convolutional Networks and End-to-End DrivingModeration: Lex FridmanLex Fridman's MIT 6.S094 lecture explains how convolutional neural networks work, where deep learning helps a self-driving car, and how to train a network to steer from video.
1:13:22ENThe Second 90%: What It Really Takes to Put Deep Learning on a Driverless CarModeration: Lex FridmanWaymo's Sacha Arnoud walks MIT students through Waymo's history, its perception stack, and the industrial-scale labeling, compute and testing behind it.
53:13ENHow Machines Learn to See: From Pixel Differences to Convolutions, ResNets and Scene SegmentationModeration: Lex FridmanLex Fridman's MIT 6.S094 lecture walks from the basics of image classification through landmark network architectures to pixel-level segmentation, optical flow and the SegFuse competition.








