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Top /r/MachineLearning Posts, November: TensorFlow, Deep Convolutional Generative Adversarial Networks, and lolz


In November on /r/MachineLearning, we've got a good laugh, a fantastic image-generating convolutional generative adversarial network, and a whole lot of Google TensorFlow.



In November on /r/MachineLearning, much of the action centers on Google's TensorFlow, its newly open-sourced machine learning framework. We also get some genuine lolz, and a paper, corresponding code, and some incredible experimental results of unsupervised representation learning with deep convolutional generative adversarial networks. Let's get to it.

1. Google TensorFlow Released +679

TensorFlow Arguably the biggest news item in the world of machine learning this month has been Google's open-sourcing of its TensorFlow library. Described as "an open source software library for numerical computation using data flow graphs," TensorFlow can execute on a wide variety of device types, from high end GPU-enabled clusters to low end mobile devices.

While the open-sourced version differs from the in-house version, notably with its single node limitation, TensorFlow is largely being well-received and will likely become a major league player in the machine learning world moving forward. The comments include some good discussion, if you have the time. You can read the TensorFlow whitepaper here, or check out its official GitHub repo here.

2. Tuesday = ( Monday + Wednesday ) / 2 +375

Not much to say, other than have a look at the image below...

Tuesday = (Monday + Wednesday)/2

3. TensorFlow Examples +248

This post shares a link to this GitHub repo, which is a collection of tutorials for TensorFlow. The tutorials are based on these Theano tutorials. Topics covered include simple multiplication, Linear regression, feedforward neural networks, and convolutional neural networks, among others.

4. Jeff Dean Explains TensorFlow +179

Here we have a video of Googler Jeff Dean giving an overview of TensorFlow, of which he is one of the designers-slash-engineers. From a talk given at a recent Bay Area Machine Learning Symposium, Jeff covers a few other topics as well, and takes some questions from the audience. The video comes before the open-sourcing announcement, and so provides a high-level overview of the system (with some foreshadowing of its recent big news). Find the video below.



5. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks +173

Generative adversarial networks creating their own image representations. I won't give away much more than that. You need to read this. It is borderline mind-blowing. The only particular aspect I'll mention is facial arithmetic.

Facial Arithmetic

You can read the full paper here.

Of related interest, a comment in the thread mentions this GitHub repo, which generates images of cats via generative adversarial networks. It includes some good explanation and discussion.

6. TensorFlow Tutorial Notebooks +158

This repo is a collection of Python notebooks, and covers the main tutorials from the TensorFlow website. It covers some introductory programs, basic classifiers, neural nets, multiple GPUs, and TensorFlow's GUI, TensorBoard.

With all of the TensorFlow material covered this month, there is no reason for you not to become an expert quickly!

Bio: Matthew Mayo is a computer science graduate student currently working on his thesis parallelizing machine learning algorithms. He is also a student of data mining, a data enthusiast, and an aspiring machine learning scientist.

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