Created by:   University of Toronto

  • Geoffrey Hinton

    Taught by:    Geoffrey Hinton, Professor

    Department of Computer Science

How To PassPass all graded assignments to complete the course.
User Ratings
4.5 stars
Average User Rating 4.5See what learners said


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How It Works

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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University of Toronto
Established in 1827, the University of Toronto has one of the strongest research and teaching faculties in North America, presenting top students at all levels with an intellectual environment unmatched in depth and breadth on any other Canadian campus.
Ratings and Reviews
Rated 4.5 out of 5 of 526 ratings

Very good and interesting introduction to neural networks. I particularly appreciated the history behind the different types of neural networks so that one understands where the basic ideas come from. I was however a bit disappointed in terms of mathematics, the course could have used a bit more mathematical formalism and some more hands on exercises. Still, I warmly recommend this course!

This is a great mathematical course to understand what's going on, but the assignments and quizzes are just repetitive and basically "run these commands." Professor Hinton definitely knows his stuff, and just sitting through his lectures was worth the time. That being said, Week 13 is busted as of 2017-1-22, Question 6 and 7 use variables values that are never mentioned. The only way I passed it was to google an old version of the course in Chinese that had a line saying "please use these other variables"

Good balance of theory, practice, historical background and humor. I finally learned how to do back-propagation on paper :)

Very good content!