From 32dda078ae62ec41da09bb641fd98f7677d94c83 Mon Sep 17 00:00:00 2001 From: Christoph Ruegg Date: Tue, 19 Aug 2014 10:04:41 +0200 Subject: [PATCH] Docs: add more blogs to Users page, move papers to the bottom --- docs/content/Users.fsx | 46 +++++++++++++++++++++++------------------- 1 file changed, 25 insertions(+), 21 deletions(-) diff --git a/docs/content/Users.fsx b/docs/content/Users.fsx index 26aa7904..08ebecba 100644 --- a/docs/content/Users.fsx +++ b/docs/content/Users.fsx @@ -29,6 +29,31 @@ Closed Source * [SpectraFox](http://www.spectrafox.com/) STM / AFM spectroscopy analysis * [Colymp](http://colymp.com/) Color Management Software +Blogs, Tutorials & Examples +--------------------------- + +* [Yin Zhu: Tutorial: Using Math.NET Numerics in F#](http://msdn.microsoft.com/en-us/library/hh304363.aspx) +* [Don Syme: Getting Started with Math.NET and F# Programming](http://blogs.msdn.com/b/dsyme/archive/2012/07/06/getting-started-with-math-net-and-f-programming.aspx) +* [Libor Tinka: Linear and Nonlinear Least-Squares with Math.NET](http://www.imagingshop.com/articles/least-squares) +* [Carl Nolan: Co-occurrence Approach to an Item Based Recommender](http://code.msdn.microsoft.com/Co-occurrence-Approach-to-57027db7) +* [Gustavo Guerra: F# as a Octave/Matlab Replacement for Machine Learning](http://functionalflow.co.uk/blog/2011/10/27/f-as-a-octavematlab-replacement-for-machine-learning/) +* [Mathias Brandewinder: Simplify data with SVD and Math.NET in F#](http://clear-lines.com/blog/post/Simplify-data-with-SVD-and-MathNET-in-FSharp.aspx) +* [Mathias Brandewinder: Recommendation Engine using Math.NET, SVD and F#](http://clear-lines.com/blog/post/Recommendation-Engine-with-SVD-and-MathNET-in-FSharp.aspx) +* [Thomas Jungblut: Stochastic Logistic Regression in F#](http://codingwiththomas.blogspot.ch/2014/05/stochastic-logistic-regression-in-f.html) +* [Calvin Bottoms: Set-Based Operations: They’re Not Just For Databases](http://calvinbottoms.blogspot.ch/2012/01/set-based-operations-theyre-not-just.html) +* [Chao-Jen Chen: F#: Simulate entire GBM path](http://programmingcradle.blogspot.ch/2012/09/f-simulate-entire-gbm-path.html) +* [Chao-Jen Chen: F#: K-S test on final prices of GBM paths ](http://programmingcradle.blogspot.ch/2012/09/f-k-s-test-on-final-prices-of-gbm-paths.html) +* [Dawid Kowalski: F#, Deedle and Computational Investing](http://dkowalski.com/blog/archive/2014/01/11/f-deedle-and-computational-investing.aspx) +* [Christoph Rüegg: Linear Regression With Math.NET Numerics](http://christoph.ruegg.name/blog/linear-regression-mathnet-numerics.html) + +Books +----- + +* Expert F# 3.0 *by Don Syme, Adam Granicz, Antonio Cisternino*. Apress. +* F# for Quantitative Finance *by Johan Astborg*. Packt Publishing. +* F# Deep Dives *by Tomas Petricek, Philip Trelford*. Manning Publications. +* Computer Graphics: Principles and Practices *by John F. Hughes, Andries van Dam, Morgan McGuire, David F. Sklar, James D. Foley, Steven K. Feiner, Kurt Akeley*. Addison-Wesley Professional, 3rd edition. + Papers and Thesis ----------------- @@ -63,25 +88,4 @@ Papers and Thesis * Hebel, Tobias (2010). *Location Provider.* Universität Koblenz Landau. * Bischoff, Sebastian (2009). *Konzeption und Umsetzung einer RIA zur untersuchungsbegleitenden Erfassung von RNFLT-Scans und Untersuchung von Klassifikatoren für die diagnostische Unterstützung bei neurodegenerativen Erkrankungen am Beispiel der Multiplen Sklerose.* Fachhochschule Brandenburg. -Blogs, Tutorials & Examples ---------------------------- - -* [Yin Zhu: Tutorial: Using Math.NET Numerics in F#](http://msdn.microsoft.com/en-us/library/hh304363.aspx) -* [Don Syme: Getting Started with Math.NET and F# Programming](http://blogs.msdn.com/b/dsyme/archive/2012/07/06/getting-started-with-math-net-and-f-programming.aspx) -* [Carl Nolan: Co-occurrence Approach to an Item Based Recommender](http://code.msdn.microsoft.com/Co-occurrence-Approach-to-57027db7) -* [Gustavo Guerra: F# as a Octave/Matlab Replacement for Machine Learning](http://functionalflow.co.uk/blog/2011/10/27/f-as-a-octavematlab-replacement-for-machine-learning/) -* [Thomas Jungblut: Stochastic Logistic Regression in F#](http://codingwiththomas.blogspot.ch/2014/05/stochastic-logistic-regression-in-f.html) -* [Calvin Bottoms: Set-Based Operations: They’re Not Just For Databases](http://calvinbottoms.blogspot.ch/2012/01/set-based-operations-theyre-not-just.html) -* [Chao-Jen Chen: F#: Simulate entire GBM path](http://programmingcradle.blogspot.ch/2012/09/f-simulate-entire-gbm-path.html) -* [Chao-Jen Chen: F#: K-S test on final prices of GBM paths ](http://programmingcradle.blogspot.ch/2012/09/f-k-s-test-on-final-prices-of-gbm-paths.html) -* [Christoph Rüegg: Linear Regression With Math.NET Numerics](http://christoph.ruegg.name/blog/linear-regression-mathnet-numerics.html) - -Books ------ - -* Expert F# 3.0 *by Don Syme, Adam Granicz, Antonio Cisternino*. Apress. -* F# for Quantitative Finance *by Johan Astborg*. Packt Publishing. -* F# Deep Dives *by Tomas Petricek, Philip Trelford*. Manning Publications. -* Computer Graphics: Principles and Practices *by John F. Hughes, Andries van Dam, Morgan McGuire, David F. Sklar, James D. Foley, Steven K. Feiner, Kurt Akeley*. Addison-Wesley Professional, 3rd edition. - *)