Show HN: Intro to Machine Learning in Interactive D3.js Visualizations
1–10 of 13 posts
Re: Show HN: Intro to Machine Learning in Interactive D3.js Visualizations
#2really 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).
Re: Show HN: Intro to Machine Learning in Interactive D3.js Visualizations
#3That'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/
Re: Show HN: Intro to Machine Learning in Interactive D3.js Visualizations
#4really 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).
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.
Re: Show HN: Intro to Machine Learning in Interactive D3.js Visualizations
#5really 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).
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.
oh for sure, just jumping in to these topics is difficult enough. i'm looking forward to what you guys put together next
Re: Show HN: Intro to Machine Learning in Interactive D3.js Visualizations
#6This is great, I can't find the source though.
Re: Show HN: Intro to Machine Learning in Interactive D3.js Visualizations
#7This is great, I can't find the source though.
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...) as well as just hanging out with the ML team at http://siftscience.com
Re: Show HN: Intro to Machine Learning in Interactive D3.js Visualizations
#8That'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 math…
Thanks Brandon! We're certainly thinking about it. We'll work out way up there.
Re: Show HN: Intro to Machine Learning in Interactive D3.js Visualizations
#9This is great, I can't find the source though.
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... ) as well as just hanging out with the ML team at http://siftscience.com
Do you have a gh repo? I really am interested in the story telling and ML aspects of the post.
Re: Show HN: Intro to Machine Learning in Interactive D3.js Visualizations
#10Earlier quoted context omitted.
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... ) as well as just hanging out with the ML team at http://siftscience.com
Do you have a gh repo? I really am interested in the story telling and ML aspects of the post.
The decision tree model was generated from 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.