xcode-select --install
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[submodule "sproutcore-examples"] | |
path = sproutcore-examples | |
url = git://github.com/rklancer/sproutcore-examples.git |
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var B = { | |
foo: function (original) { | |
console.log("Foo B"); | |
original(); | |
}.enhance() | |
}; | |
var C = { | |
foo: function () { | |
console.log("Foo C"); |
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/*globals MyApp*/ | |
MyApp.ColorPicker = SC.PickerPane.design({ | |
layout: { width: 250, height: 195 }, | |
theme: "popover", | |
contentView: SC.WorkspaceView.design({ | |
topToolbar: SC.ToolbarView.design({ | |
layout: { top: 0, left: 0, right: 0, height: 32 }, | |
childViews: "label colorSwatch".w(), |
UPDATE a fork of this gist has been used as a starting point for a community-maintained "awesome" list: machine-learning-with-ruby Please look here for the most up-to-date info!
- liblinear-ruby: Ruby interface to LIBLINEAR using SWIG
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require 'classifier' | |
robot_overlord = Classifier::Bayes.new 'hilton', 'franklin' | |
robot_overlord.train_hilton("The only rule is don't be boring and dress cute wherever you go. Life is too short to blend in.") | |
robot_overlord.train_hilton("The way I see it, you should live everyday like its your birthday.") | |
robot_overlord.train_hilton("No matter what a woman looks like, if she's confident, she's sexy.") | |
robot_overlord.train_hilton("I'd imagine my wedding as a fairy tale... huge, beautiful and white.") | |
robot_overlord.train_hilton("There's nobody in the world like me. I think every decade has an iconic blonde, like Marilyn Monroe or Princess Diana and, right now, I'm that icon.") | |
robot_overlord.train_hilton("Some girls are just born with glitter in their veins.") |
Fast/efficient approach:
-- execute("UPDATE posts SET comments_count = (SELECT count(1) FROM comments WHERE comments.post_id = posts.id)")
-> 1.3197s
Slow/naïve approach:
If you have any sort of administrative interface on your web site, you can easily imagine an intruder gaining access and mucking about. How do you know the extent of the damage? Adding an audit log to your app is one quick solution. An audit log should record a few things:
- controller entry points with parameter values
- permanent information about the user, like user_id
- transient information about the user, like IP and user_agent
Using the Rails framework, this is as simple as adding a before_action
to your admin controllers. Here’s a basic version that I’m using in production.
Taught by Brad Knox at the MIT Media Lab in 2014. Course website. Lecture and visiting speaker notes.
- Power to the People: The Role of Humans in Interactive Machine Learning by Knox, Cakmak, Kulesza, Amershi, and Lau
- A Few Useful Things to Know about Machine Learning by Domingos
- Machine Learning that Matters by Wagstaff
- Beyond Concise and Colorful: Learning Intelligible Rules by Pazzani et al.
- [Designing Games with a Purpose] (https://www.cs.cmu.edu/~biglou/GWAP_CACM.pdf) by von Ahn and Dabbish
- [Human Model Evaluation in Interactive Supervised
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