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Algorithm Tutorials - Vimperator

Algorithm Tutorials - Vimperator

Martin Fowler: Articles Popular Some articles keep showing up as regular choices for visitors. So I thought I'd put them first in case you're looking for them, or if not to see what counts as popular around here. The New Methodology In the past few years there's been a blossoming of a new style of software methodology - referred to as agile methods. Latest Significant Version: 2005-12-13 Is Design Dead? For many that come briefly into contact with Extreme Programming, it seems that XP calls for the death of software design. Latest Significant Version: May 2004 Continuous Integration Continuous Integration is a software development practice where members of a team integrate their work frequently, usually each person integrates at least daily - leading to multiple integrations per day. Latest Significant Version: 2006-05-01 Inversion of Control Containers and the Dependency Injection pattern Enterprise Application Architecture For most of my career I've specialized in enterprise application work. Mocks Aren't Stubs Range

What algorithm BLOWS YOUR MIND? : compsci Antoniak: Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems A random process called the Dirichlet process whose sample functions are almost surely probability measures has been proposed by Ferguson as an approach to analyzing nonparametric problems from a Bayesian viewpoint. An important result obtained by Ferguson in this approach is that if observations are made on a random variable whose distribution is a random sample function of a Dirichlet process, then the conditional distribution of the random measure can be easily calculated, and is again a Dirichlet process. This paper extends Ferguson's result to cases where the random measure is a mixing distribution for a parameter which determines the distribution from which observations are made. The conditional distribution of the random measure, given the observations, is no longer that of a simple Dirichlet process, but can be described as being a mixture of Dirichlet processes.

Genetic Algorithm For Hello World This article works through the creation of a ‘toy’ genetic algorithm which starts with a few hundred random strings and evolves towards the phrase “Hello World!”. It’s a toy example because we know in advance what the optimum solution is – the phrase “Hello World!” – but it provides a nice simple introduction to evolutionary algorithms. I have written this article primarily for developers who have a casual interest in machine learning. I don’t talk much about the implementation of the code itself because there’s not much of interest there – the beauty of genetic algorithms is their simplicity, so the code isn’t that interesting, other than in as much as it’s not usual to do such things in JavaScript. In short, a typical genetic algorithm works like this: Represent solutions as binary strings (called chromosomes). In more detail, genetic algorithms are comprised of the following concepts: Now let’s work through a specific problem – the genetic Hello World algorithm: The Fitness Function

Hidden Video Courses in Math, Science, and Engineering » Data Wrangling Blog Hidden Video Courses in Math, Science, and Engineering Over the last few years, a large number of open courseware directories and video lecture aggregators have popped up on the web. These sites often include introductory courses and research seminars, but it can be difficult to find full courses covering advanced topics. What motivated me to pull this together? It is difficult to find advanced math and physics courses that fit into a full time work schedule. The approach I came up with was to load an Archos video player with video lectures from the web (an iphone would probably work just as well). Most video players now come with wifi built in, so if you have wireless access at your gym you should be ready to go. Enough motivation, on with the links: Links to Advanced Courses with Complete Video Lectures: Update (02/10/09): I've bookmarked 20 new video courses since the original post was published on April 09, 2008. Physics Mathematics Computer Science & Engineering Machine Learning

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