Caffeinated Simpleton » Blog Archive » Fifth: Static Storage and
clojure setup So it turns out getting set up to write Clojure code can be a little tricky. There are a lot of disconnected tidbits about how folks have figured out how to configure things, but it can be a bit tricky to tell the difference between, "hey, this is how I finally got it to work" and "this is how you really should be doing it". I figure I know about as much about using Clojure with Emacs as anybody, so here's a run-through of how I've done my setup. There are a lot of moving parts, but bear with me; most of the installation is automated. Spoiler Alert: Using SLIME with Clojure is now much easier than the instructions detailed below indicate. clojure setup
Leiningen Emacs ELPA slime/swank install problems - Cloj Hi all, I recently started playing with leiningen, and it looks like it's going to help remove a lot of the incidental complexity in getting projects started with clojure! However I had some what of a hard time getting it going with Emacs/clojure-mode/slime... This is likely because clojure-mode/slime/swank evolve more quickly than I keep up, but that in itself is a problem... especially when there's little google-able discussion on the recomended methods online. Anyway I finally seem to have got things worked out... so I thought I'd document here what I tried... Perhaps this'll be useful to others. Leiningen Emacs ELPA slime/swank install problems - Cloj
Leiningen Emacs ELPA slime/swank install problems - Cloj Leiningen Emacs ELPA slime/swank install problems - Cloj Hi all, I recently started playing with leiningen, and it looks like it's going to help remove a lot of the incidental complexity in getting projects started with clojure! However I had some what of a hard time getting it going with Emacs/clojure-mode/slime...
Caffeinated Simpleton » Blog Archive » Fifth: Static Storage a
pcollections - Google Code
README.rst Tokyo Cabinet for Clojure Introduction brool's tokyo-cabinet at master - GitHub brool's tokyo-cabinet at master - GitHub
clojure rich hickey datatypes > I'm still trying to get my head around the new features. Seeing more > code examples will definitely help. In the meantime, here is some > stream-of-consciousness thoughts and questions. > > Datatypes: > > I'm a little worried about the strong overlap between reify/proxy, > deftype/defstruct, and defclass/gen-class. clojure rich hickey datatypes
Clojars and Leiningen Automate Library and Dependency Management Clojars and Leiningen Automate Library and Dependency Management Using libraries is easy but getting all the right ones onto your system can be a pain. Many languages solve the problem with repositories that host the libraries + metadata and tools that make it easy to pull the right versions of the libraries. In the Ruby space the solution is Ruby Gems, both a tool and packaging format; a default repository hosted at Rubyforge (Gems hosting will soon move to the GemCutter system, which offers more flexibility) makes it єasy to publish and consume Gems. In the Java space, Maven is a popular solution. Clojars is a new repository that aims to make it easy to share and consume Clojure libraries. A Clojure specific build tool called Leiningen, created by Phil Hagelberg, makes it easy for producers to bundle and push Clojure libraries to Clojars, and for consumers to pull them and make sure they're in the right default place for Clojure programs.
I originally wrote this in a Google Groups thread, but I figured it’s worth repeating here. Somebody posted a Java and Clojure snippet to the Clojure Google group and mentioned that the Java code was vastly faster than the Clojure code and he wondered if Clojure could get within reach of Java’s speed. In my own clj-starcraft project, I faced — and actually, still face — performance problems vis-à-vis Java. Specifically, at the time of this writing, my Clojure code is roughly 6 times slower than Java (Clojure takes around 70 seconds to parse 1,050 files, Java takes 12.) Clojure performance tips « Occasionally sane Clojure performance tips « Occasionally sane
Datatypes and Protocols - early experience program - Clojure | G Datatypes and Protocols - early experience program - Clojure | G > I'm still trying to get my head around the new features. Seeing more > code examples will definitely help. In the meantime, here is some > stream-of-consciousness thoughts and questions. > > Datatypes: > > I'm a little worried about the strong overlap between reify/proxy, > deftype/defstruct, and defclass/gen-class. I can just imagine the > questions a year from now when people join the Clojure community and > want to understand how they differ. So I think that eventually, there > needs to be a very clear "story" as to why you'd choose one over the > other.
I’ve been playing with Tokyo Cabinet and Clojure for a bit, and while I will go on about both of them in another blog post (or not), I have to mention that Clojure is such a well designed language that it’s a pleasure to play with. It has much of the same intrinsic power as Haskell, but in a fashion that might be more approachable for people coming from Python or Ruby. At any rate, I made a small, thin layer around the Tokyo Cabinet API, and put it on Github. brool » Tokyo Cabinet API for Clojure brool » Tokyo Cabinet API for Clojure

Object Computing, Inc. - Java News Brief - March 2009

by R. Mark Volkmann, Partner Object Computing, Inc. (OCI) last updated on 6/2/13 Object Computing, Inc. - Java News Brief - March 2009
Online Learning is a relatively old branch of machine learning that has recently regained favour for two reasons. Firstly, online learning algorithms such as Stochastic Gradient Descent work extremely well on very large data sets which have become increasingly prevalent (and increasingly large!). Secondly, there has been a lot of important theoretical steps made recently in understand the convergence behaviour of these algorithms and their relationship to traditional Empirical Risk Minimisation (ERM) algorithms such as Support Vector Machines (SVMs). Online Learning in Clojure ← Structure & Process
Statistical Learning in Clojure Part 1: LDA & QDA Classifier This will hopefully be the first of a series of posts based on a book that has substantially influenced me over the last several years, The Elements of Statistical Learning (EoSL) by Hastie, Tibshirani, and Friedman (I went and got a degree in statistics essentially for the purposes of better understanding this book). Best of all, the pdf version of EoSL is now available free of charge at the book’s website, along with data, code, errata, and more. This post will demonstrate the use of Linear Discriminant Analysis and Quadratric Discriminant Analysis for classification, as described in chapter 4, “Linear Methods for Classification”, of EoSL. I will implement the classifiers in Clojure and Incanter, and use the same data set as EoSL to train and test them.
Chaos Theory vs Clojure « Best In Class – The Blog
Clojure is a dynamic programming language that targets the Java Virtual Machine (and the CLR, and JavaScript). It is designed to be a general-purpose language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. Clojure is a compiled language - it compiles directly to JVM bytecode, yet remains completely dynamic. Every feature supported by Clojure is supported at runtime. Clojure provides easy access to the Java frameworks, with optional type hints and type inference, to ensure that calls to Java can avoid reflection.

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Using Clojure as an embedded / hosted scripting language - Cloju