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: http://bit.ly/2H8Fs7g
Website: https://deeplearning.mit.edu
GitHub: https://github.com/lexfridman/mit-dee...
Playlist: https://goo.gl/SLCb1y

Links to individual lecture videos for the course:

Lecture 1: Introduction to Deep Learning and Self-Driving Cars
   • MIT 6.S094: Introduction to Deep Lear...  

Lecture 2: Deep Reinforcement Learning for Motion Planning
   • MIT 6.S094: Deep Reinforcement Learni...  

Lecture 3: Convolutional Neural Networks for End-to-End Learning of the Driving Task
   • MIT 6.S094: Convolutional Neural Netw...  

Lecture 4: Recurrent Neural Networks for Steering through Time
   • MIT 6.S094: Recurrent Neural Networks...  

Lecture 5: Deep Learning for Human-Centered Semi-Autonomous Vehicles
   • MIT 6.S094: Deep Learning for Human-C...  

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