Deep Learning for Self-Driving Cars

Lex Fridman, MIT

This class is an introduction to the practice of deep learning through the applied theme of building a self-driving car. It is open to beginners and is designed for those who are new to machine learning, but it can also benefit advanced researchers in the field looking for a practical overview of deep learning methods and their application.

Course Topics:

* Material marked in red indicates links that are not yet active but will soon be.

  • Introduction to Deep Learning and Self-Driving Cars
    [ Slides ] - [ Lecture Video ]
  • Learning to Move: Deep Reinforcement Learning for Motion Planning
    [ Slides ] - [ Lecture Video ]
  • Learning to Drive: Convolutional Neural Networks and End-to-End Learning of the Full Driving Task
    [ Slides ] - [ Lecture Video ]
  • Learning to Share: Driver State Detection and Shared Autonomy
    [ Slides ] - [ Lecture Video ]
  • Learning to Think: The Road Ahead for Human-Centered Artificial Intelligence
    [ Slides ] - [ Lecture Video ]

Guest Speakers:

From Research to Reality: Testing Self-Driving Cars on Public Roads
CEO, nuTonomy and Research Scientist, MIT
Self-Driving Vehicles, SLAM, and Deep Learning
Professor, MIT
Technology, Policy and Vehicle Safety in the Age of AI
Professor, Stanford
Past, Present, and Future of Motion Planning in a Complex World
Professor, MIT
We Only Adopt What We Trust: Policy and the Business of Autonomy
White House Presidential Innovation Fellow, Office of Science and Technology Policy

Schedule:

会期:
  • 2017年1月09日, 2 星期
介绍:
  • 免费:
  • 收费:
  • 证书:
  • MOOC:
  • 视频讲座:
  • 音频讲座:
  • Email-课程:
  • 语言: 英语 Gb

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