Emore

When future-you wishes present-you had done the thing. So in a sense there is a you (future-you) that actually does want to do the thing.

Oink's Pink Palace. Yes it was a torrent tracker so arguably illegal, but the breadth and depth of music it cataloged (not to speak of the community) is still unmatched.

Or you can just ask. I emailed asking for a refund, citing corona, the (pre-paid, non-refundable) hotel I was going to stay at for SXSW and they refunded me the entire sum. Very impressed, and I'm sure preferable to credit card charge backs.

The Sandbaggers is amazing; I found it to be more memorable and "realistic" (not that I could know) than le Carré.

Also, all episodes are on YouTube: https://www.youtube.com/watch?v=lKg_t-Prhqk&list=PLmRu2axUu2...

I wrote a machine learning cheat sheet once, as a way to learn when I was in your seat: http://eferm.com/machine-learning-cheat-sheet/

Perhaps the cheat sheet in itself is useful for you, but mostly I'd recommend the process of assembling information in a concise way as a good way to learn.

I believe it's Paper for iPad: https://itunes.apple.com/us/app/paper-by-fiftythree/id506003...

Yes, a thousand times yes. I have never understood why dependency injection is not taught in OOP courses -- as described in the article, DI truly shows why OOP design is useful. Conversely, the "domain model"-approach commonly used probably gains some of its attraction due to the similarities to E/R database diagrams, but far from always lead to designs which are actually useful in practice.

Nice! I've been using Arq for some time and it's great for selective backup (I use Backblaze for bulk backups.) Stefan, the developer of Arq, is also quick to reply and very helpful.

"-So, where are you taking Facebook at this point? Are you going to expand to those other schools that you're not at? And then, what?"

"-I mean, there doesn't necessarily have to be more. Like, a lot of people are focused on taking over the world ... part of making a difference and making something cool is focusing intensely."

Whoa. Sean Parker really changed him. Joking aside, I wonder at what point MZ started to considering taking over the world for real.

Anyone know why an OS X release is not on the list?

As a computer scientist, one wonders what kind of randomness? Is the date picked uniformly at random, or is there a bias involved (for example, a negative bias towards the coming days)?

For me, Xcode 4.1 removed gcc-4.0 (needed by brew for example). If you had Xcode 3.x it's still in /Developer-old, and can be re-added with ln -s /Developer-old/usr/bin/gcc-4.0 /usr/bin/gcc-4.0.

Homebrew works, after you run 'brew update' (in case you haven't already, I'm guessing). Initially got erros 'Cannot defer diagnostic messages' for pr, but updated brew seems to be working well.

If you search for "Lion" it's there. It doesn't seem to be under "Featured" yet.

It's available globally. At least if I'm allowed to extrapolate from {US, UK, Sweden}.

Sorry for the late reply. Here are my details:

Mac OS X 10.6.8 all updated / Google Chrome 12.0.742.122 / MacBookAir3,2 / 2.13 GHz / 4GB RAM

Would be interesting to know if you have, indeed, found an exploitable driver bugs.

(Repeated) kernel panic on Macbook Air/Chrome I'm afraid.

A guess: some major browser's search bar started to parse "facebook.com" as a domain rather than a search term?

Cool, didn't know about these publications (I'm at the Comlab myself.)

Seems like the webpage to sign up for the newsletters (by email!) is http://www.cs.ox.ac.uk/industry/public/newsletter.jsp

Here's another one, a simple Applet that lets you apply various classification algorithms on 2D data: http://www.cs.technion.ac.il/~rani/LocBoost/

For the record, the Google exec (Berthier Ribeiro-Neto) is the co-author of "Modern Information Retrieval" [1], an excellent book and close to a standard text on IR.

[1] http://www.amazon.com/Modern-Information-Retrieval-Ricardo-B...

Perhaps only tangentially relevant, but as they snarkily say here in Oxford: When you graduate as a Rhodes scholar you know your best days are behind you.

@sghemawat: Are you planning on implementing atomic CAS operations?

Thanks for the comments!

The course unfortunately couldn't cover all material on all algorithms, so the cheat sheet basically reflects my own knowledge rather than what's possible. I've referenced the Online SVM and Online Mixture model though, thanks for those.

Also, I'll have to look into stochastic gradient descent!

Thanks for the comments!

Good point about using cross-validation to learn K, I forgot about that. I added this to the cheat sheet.

Also regarding online learning methods, I was probably a bit quick to dismiss certain algorithms as not supporting online learning; in coursework we unfortunately didn't have time to delve into all aspects of all algorithms. I've rewritten the Online column as "To be added." for those online methods I'm not familiar with (yet). Someone else is, of course, free to fork it on Github: http://github.com/Emore/mlcheatsheet

Thanks for the feedback!

I've changed the title to "Algorithms for Supervised- and Unsupervised Learning", which is definitely more appropriate. Initially the cheat sheet only contained linear classifiers, hence the misleading title.

One US helicopter went down. Probably the one tweeted about.

http://english.aljazeera.net/indepth/2011/05/201152619612164...