Archive

The ToroDB solution to provide better analytics on top of MongoDB and make it easier to migrate from MongoDB to SQL

<blockquote>Xidel is a command line tool to download html/xml pages and extract data from them using CSS 3 selectors, XPath 2 expressions or pattern-matching templates.</blockquote>

Internet search, speech recognition, machine translation, question answering, information retrieval, biological sequence analysis -- are all at the forefront of this century’s information revolution. In addition to their use of machine learning, these technologies rely heavily on classic statistical estimation techniques. Yet most CS and engineering undergraduate programs do not prepare students in this area beyond an introductory probability & statistics course. This course is designed to address this gap.

The goal of "Language and Statistics" is to ground the data-driven techniques used in language technologies in sound statistical methodology. We start by formulating various language technology problems in both an information theoretic framework (the source-channel paradigm) and a Bayesian framework (the Bayes classifier). We then discuss the statistical properties of words, sentences, documents and whole languages, and the various computational formalisms used to represent language. These discussions naturally lead to specific concepts in statistical estimation.

Machine Learning (ML) asks "how can we design programs that automatically improve their performance through experience?" This includes learning to perform many types of tasks based on many types of experience, e.g. spotting high-risk medical patients, recognizing speech, classifying text documents, detecting credit card fraud, or driving autonomous robots.

Topics covered in 10-601A include concept learning, version spaces, decision trees, neural networks, computational learning theory, active learning, estimation & the bias-variance tradeoff, hypothesis testing, Bayesian learning, the Minimum Description Length principle, the Gibbs classifier, Naïve Bayes classifier, Bayes Nets & Graphical Models, the EM algorithm, Hidden Markov Models, K-Nearest-Neighbors and nonparametric learning, reinforcement learning, genetic algorithms, bagging and boosting.

Kylin is an open source Distributed Analytical Engine from eBay Inc. to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop to support extremely large petabytes of data analysis.

meta links about nixos

Links to writings of David Foster Wallace

When I say "Monads aren't difficult, and you are smart enough to understand them," I'm now going to link to

with solutions

Just the facts on what needs to be done to your SSL certificate.
Designed for Heroku, but works for any webapp

understand how they were consistently performing well in competitions.

xmlstarlet sel -t -m "/rhythmdb/entry[@type='iradio']" -v title -n -v location -n ~/.local/share/rhythmbox/rhythmdb.xml

h/t to @cemerick, he just showed me this and you need to basically watch every single video:

The Memory Pool System is a flexible and adaptable memory manager. Among its many advantages are an incremental garbage collector with very low pause times, and an extremely robust implementation. It's both open source and commercially licensed.

recommended on #haskell-beginners via https://gist.github.com/bitemyapp/8739525

mention of some other command line libraries.

syllabus to read Types and Programming Language by Pierce