Final flurry of Stanford-related links

Here is a fantastic compendium of "nature-inspired" AI algorithms, each described with pseudocode and Ruby. It's this kind of thorough survey work that really makes my world go round.

NLP

I decided against Stanford's online AI class, but their NLP class has a nice set of notes that would probably be worth working through in the same sort of way as I intend to do for machine learning.

They're here.

Machine learning

So as I mentioned earlier, I'm going to be working through Stanford's online machine learning course this fall. I expect there to be a lot of things I'll want to work into Decl and its approach.

The class itself is here; I've also got some supporting links I'll want to keep track of:

• BYU's machine learning and data mining course.
• Book: The Elements of Machine Learning. More math, I think.
• Octave documentation.
• Reddit on Machine Learning and on this class.

Ideally, I'd like to have a toolset of reusable tools that was literate-programmed using Decl when I'm finished with this course. Might be too ambitious, but we'll see.

Sending email: best practices

When sending email from a host, here are the things you want to do to avoid getting onto anybody's block list. Good luck on that.

Target application: Promoter

This is a great example of a simple, clear, well-implemented application that represents the kind of thing I want to be aiming for. It combines a database with Web monitoring. Perfect.

haXe

haXe is the follow-on for the Ming SWF library; instead of compiling Actionscript, they decided just to define their own language that could then compile to SWF, Javascript, and some other stuff.

I find that a tad irritating because I'd like to have something that could compile Actionscript 3.0 into SWF for me that was open-source, but the effort itself is pretty cool and worth looking at.

Diagramming again

Along with Octave, I've been thinking that presentation of systems might benefit from a diagramming language. Not that this is a new thing for me; it recurs with tiresome periodicity, actually.

But this is its first recurrence since I have a pseudocode parser at the ready.

So I've been looking at different diagramming systems for inspiration. I'm not even primarily interested in a diagram editor - just a display based on a structural language. Like graphviz, really. I could see diagrams being editable later, and I could certainly see them being clickable links in a system description or the like, but right now my primary focus is typesetting of readable documents, I think.

This post has been pretty thin in terms of doing anything except establishing a point of interest, hasn't it?

TeX

I've been meaning to get back to TeX lately, for two reasons. First, my wife is doing things with physics that need to be typeset, and second, TeX has some pretty neat diagramming tools, like xy-pic.

The only problem with xy-pic (and with TeX in general) is that it's syntactically unreadable. I am so terribly uninterested in decoding @{0->}<>33x\dot or whatever, and so again I say "Decl macro system".

So I'm mulling over kind of a TeX/wiki mashup, I guess. More on that later, I suppose.

Octave

I've enrolled in the Stanford online machine learning course, and even before it's started it's making me think. It looks as though Octave will figure strongly in the course.

Octave has a pretty groovy set of capabilities, but I'm just not the unadorned command line kind of guy. I'm sure I'll be mostly running Octave on files. And here's the thing - what I really want to do with that is to generate the Octave code from Decl, because I'd like to be able to generate presentations from the same code, keep data in databases, and so forth. (Actually, I believe Octave knows how to talk to databases, but still.)

So I'm looking at Inline::Octave and we'll see how that works out. This is also a natural place to finish my macro system, which seems to have run aground again. Literate Octave programming.

Learn REST: blog post series

The title kind of says everything it needs to.

DevOps choices at AppNexus

I don't even know what AppNexus is, but they need to scale, and their devops infrastructure is outlined in a handy-dandy blog post here.

Open source targets: BuddyPress and CUNY Academic Commons

BuddyPress is a WordPress plugin that implements a social network. It's used as the platform for the CUNY Academic Commons, an open-source platform for, well, academics at CUNY. It would be nice to help out open-source projects where possible, so this would be one place to start.

Draw a Stick Man

Very neat HTML Canvas design. [hnn] You could really imagine all kinds of storytelling on a platform like this.

Ticket Servers: Distributed Unique Primary Keys on the Cheap

A nice trick they use over at Flickr to get unique keys using a simple MySQL instance.

This prompts me again to muse about an infrastructure description language.

Real time face substitution

Very cool! This tool finds the face in a video feed in real time and substitutes it - kind of - with another face assembled from stock photos or whatever. It's ... uncanny valley squared.

But it's interesting, because it uses something called openFrameworks (a C++ library for creative work) as a platform, then combines it with FaceTracker (a C++ library for ... face tracking) and an image cloning library that looks pretty rad, too.

All of that is pretty neat stuff, so I wanted to bookmark it.

mrjob

Yelp has a parallel job framework called "mrjob" - no, not Mr. Job, but map-reduce job - that currently only supports Python but that could be used to manage map-reduce jobs in any language.

Might be cool to try that with Perl.

NLP

At some point I'm just going to have to start, but:

• NLTK, and a list of suggested NLTK projects for further thought
• OpenNLP is an umbrella project for all kinds of NLP open-source projects
• ClearTK is a Java-based NLP library
• LingPipe ditto
• GATE ditto
• Xerox has a finite-state tool

OK, so here's the idea, and it's always the same idea. In a given NLP-domain problem, I'd model the data and the toolchain in Decl. Thus given a problem, you'd state the problem in Decl, and refine your solution progressively, always keeping the Decl semantic structure for the problem intact at each step. Here, it's almost a note-taking or documentation tool; the actual program would be written in Python and/or Java and invoked by Decl. It could also be embedded, of course, via Inline - but the point is that Decl needn't be seen as an exclusively Perl-based tool. It's also a litprog tool that can use macros to build anything else.

Ah, well. That's probably not all too clear. I'm tired.

What prompted this flurry of NLP searching was this Yelp blog post about a data set they're releasing to researchers.

Book: Mining of Massive Datasets

A Stanford book/course on the topic named. I should really just work through the thing.

Rhetorical analysis

I'm not even sure how the analysis of rhetoric fits into semantic programming, except that (1) it's NLP kind of, (2) it's research and therefore database-oriented kind of, and (3) I keep coming back to it.

The trigger is an article on CNN [HNN discussion] by Bill Bennett of the Claremont Institute tearing down the concept of spending public money on education (god forbid the teacher's unions should get tax money). There are a few little nasty tricks he throws in. I think it would be possible to analyze this kind of rhetorical treatment, maybe. Eventually. I'm not sure how to start, but it fascinates me.

Anyway, the article just pissed me off, so I thought I'd bookmark the stuff with this post.

Slick Perl trick: "enchantment" of coderefs

I should do this throughout Decl, actually: equip coderefs with debugging facilities. [monks] [another post]