Quoc Le’s Lectures on Deep Learning

Update:  Dr. Le has posted tutorials on this topic: Part 1 and Part 2.

Dr. Quoc Le from the Google Brain project team (yes, the one that made headlines for creating a cat recognizer) presented a series of lectures at the Machine Learning Summer School (MLSS ’14) in Pittsburgh this week. This is my favorite lecture series from the event till now and I was glad to be able to attend them.

The good news is that the organizers have made available the entire set of video lectures in 4K for you to watch. But since Dr. Le did most of them on the board and did not provide any accompanying slides, I decided to put the contents of the lectures along with the videos here.

In this post I posted Dr. Le’s lecture videos and added content links with short descriptions to help you navigate them better.

Lecture 1: Neural Networks Review

[JavaScript needed to view this video.]

Dr. Le begins his lecture starting from the fundamentals on Neural Networks if you’d like to brush up your knowledge about them. Otherwise feel free to quickly skim through the initial sections but I promise there are interesting things later on. You may use the links below to quickly skip the video to the relevant parts. Let me know in the comments if they don’t work.


Lecture 2: NNs in Practice

[JavaScript needed to view this video.]

If you have already covered NN in the past then the first lecture may have been a bit dry for you but the real fun begins in this lecture when Dr. Le starts talking about his experiences of using deep learning in practice.


Lecture 3: Deep NN Architectures

[JavaScript needed to view this video.]

In this lecture, Dr. Le finishes his description on NN architectures. He also talks a bit about how they are being used at Google for applications in image and speech recognition, and language modelling.


25 thoughts on “Quoc Le’s Lectures on Deep Learning”

  1. Pingback: Four short links: 14 July 2014 | Big Data 2014
  2. His introduction of word representation by Tomos Mikolov is not accurate. He should read more carefully about Tomos work before giving lecture.

Leave a Reply

Your email address will not be published. Required fields are marked *