
Show HN: Intro to Machine Learning in Interactive D3.js Visualizations - tonyhschu
http://www.r2d3.us/visual-intro-to-machine-learning-part-1/
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brandonb
That's an incredibly good visualization! Both beautiful and clear. Next time
I'm explaining machine learning to somebody who's smart but not a computer
scientist or statistician, this is where I'll start.

Do you think a future tutorial could demystify deep learning and neural
networks? Many people are confused by the backpropgation algorithm, but the
way it works is simple and intuitive if you can get beyond the mathematical
notation. The way that errors propagate backwards through the neural network
is not all that dissimilar from the data flow in your "Growing a tree"
section.

Andrej Karpathy has a great library that trains neural networks directly in
the browser: cs.stanford.edu/people/karpathy/convnetjs/

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tonyhschu
Thanks Brandon! We're certainly thinking about it. We'll work out way up
there.

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therobot24
really nice visual, it'd be cool to see similar illustrations for areas of ML
that do more than just separate classes based on a set of features, rather
work with your data in more interesting ways (e.g., CNNs learning features,
semi-supervised methods for training with unlabelled data, and subspace
techniques like CCA that work on a projected version of your data).

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tonyhschu
Thanks! Yeah absolutely. We are working our way up to those. Our tentative
plan is to tackle bias-variance trade-off next, then random forests, then
neural networks.

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therobot24
oh for sure, just jumping in to these topics is difficult enough. i'm looking
forward to what you guys put together next

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chrisgd
Really cool. As someone who didn't fully understand what people mean by
machine learning, this is great.

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leekh
This is great, I can't find the source though.

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tonyhschu
OP here. What kinds of sources are you looking for? We built this based on
some of the lectures in Stanford's statistical learning class
([http://online.stanford.edu/course/statistical-learning-
winte...](http://online.stanford.edu/course/statistical-learning-winter-2014))
as well as just hanging out with the ML team at
[http://siftscience.com](http://siftscience.com)

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leekh
Do you have a gh repo? I really am interested in the story telling and ML
aspects of the post.

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tonyhschu
The decision tree model was generated from [http://scikit-
learn.org](http://scikit-learn.org) in Python. The JS is a complete mess, but
I'll try to write up how it works in the next couple days.

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imh
I'd love to see the JS too. Great viz!

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rpglover64
Any chance of an RSS feed?

