Quoc Le’s Lectures on Deep Learning

· Posted in Machine Learning, Talks

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

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Dr. Le begins his lecture starting from the fundamentals on Neural Networks in case you’d like to brush up your knowledge about them. Otherwise feel free to quickly skim through 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.

Contents


Lecture 2: NNs in Practice

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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.

Contents


Lecture 3: Deep NN Architectures

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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.

Contents



9 Responses to “Quoc Le’s Lectures on Deep Learning”

  1. jiechen

    good,studying

    Reply
  2. Saw shen

    Nice

    Reply
  3. auraham

    great job! I will watch it

    Reply
  4. seno chow

    watch it

    Reply
  5. xu

    watch it

    Reply
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  9. Yikun

    His introduction of word representation by Tomos Mikolov is not accurate. He should read more carefully about Tomos work before giving lecture.

    Reply

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