Blog articles tagged 'f#', 'algorithms'

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on 12/26/2016 9:07 PM
So, continuing where we left off: Walking the Euler Path: Intro Visualizing Graphs Walking the Euler Path: GPU for the Road Walking the Euler Path: PIN Cracking and DNA Sequencing For the Win And finally I ran the GPU-enabled algorithm for finding the Eul[...]
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on 12/23/2016 3:17 AM
It’s that time of the year again where F#ers come together and write a bit about what they enjoy. I really enjoyed this years Advent of code and while I only did a few of the exercises in F# I want to write about one algorithm that helped out in quite a f[...]
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on 11/8/2016 10:22 PM
Continuing on to some cool applications of Eulerian paths. Intro Visualization GPU/CUDA Injection The goal of this little graph experiment remains exploration of accelerating Eulerian path finding on the GPU. This is the final introductory post. Eulerian [...]
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on 5/17/2015 3:22 PM
The Problem “Motif finding is a problem of finding common substrings of specified length in a set of strings. In bioinformatics, this is useful for finding transcription binding sites” (recap here). The problem is succinctly stated on Rosalind. Given a se[...]
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on 12/7/2014 1:11 AM
This post is for the 7th day of the 2014 F# Advent Calendar. It has been said that functional languages can’t be as fast as their imperative cousins because of all of the allocation and garbage collection, this is patently false (as far as F# is concerned[...]
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on 6/17/2014 4:15 AM
Like many a good man, I too got caught into the 2048 trap, which explains in part why I have been rather quiet on this blog lately (there are a couple other reasons, too). In case you don't know what 2048 is yet, first, consider yourself lucky - and, fa[...]
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on 4/26/2014 6:42 AM
Recently Scott Wlaschin blogged an excellent post “Twenty six low-risk ways to use F# at work” with guides and samples of how to improve your productivity at work with some of F# tips. But how to train your F# skills? Yes, the best answer is to read excel[...]
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on 2/15/2014 5:51 PM
My favorite column in MSDN Magazine is Test Run; it was originally focused on testing, but the author, James McCaffrey, has been focusing lately on topics revolving around numeric optimization and machine learning, presenting a variety of methods and appr[...]
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on 7/5/2013 9:51 PM
Besides having one of the coolest names around, Random Forest is an interesting machine learning algorithm, for a few reasons. It is applicable to a large range of classification problems, isn’t prone to over-fitting, can produce good quality metrics as a[...]
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on 9/27/2011 6:15 AM
While writing the previous article on tokenized matching I realized I left out some important background information on Jaro-Winkler distance. First, there’s something important to know about the Jaro-Winkler distance: it’s not a metric distance and so do[...]
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