This is lecture 2 of course 6.S094: Deep Learning for Self-Driving Cars taught in Winter 2017. This lecture introduces types of machine learning, the neuron as a computational building block for neural nets, q-learning, deep reinforcement learning, and the DeepTraffic simulation that utilizes deep reinforcement learning for the motion planning task.
INFO:
Slides: [ Ссылка ]
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Links to individual lecture videos for the course:
Lecture 1: Introduction to Deep Learning and Self-Driving Cars
[ Ссылка ]
Lecture 2: Deep Reinforcement Learning for Motion Planning
[ Ссылка ]
Lecture 3: Convolutional Neural Networks for End-to-End Learning of the Driving Task
[ Ссылка ]
Lecture 4: Recurrent Neural Networks for Steering through Time
[ Ссылка ]
Lecture 5: Deep Learning for Human-Centered Semi-Autonomous Vehicles
[ Ссылка ]
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