@ JuliaTokyo #1 http://juliatokyo.connpass.com/event/6891/
Working on numerical problems daily, I have always dreamt of a language that provides an elegant interface while allowing me to write codes that run blazingly fast on large data sets. Julia is a language that turns this dream into a reality. With Julia, you can focus on your problem, keep your codes clean, and more importantly, write fast codes without diving into lower level languages such as C o
Python v. Clojure v. Julia a contest of text and grouping! tl;dr: We compare Python performance against Clojure, Julia, and Java in text-processing and dynamic collections. Remarkably, Python does well. Note - this post embeds gists for code. These do not render well on Planet pages or on RSS readers like feedly. It may be better to view on the original site Situation I mostly understand numeric p
Join us for the largest Julia Programming Language event of the year!
I am Pontus Stenetorp,* a researcher and educator that finds Natural Language Processing (NLP) and Machine Learning research to be fascinating. The widely-adopted text annotation and visualisation tool brat is one of my creations and since 2012 a majority of my work has been on representation learning (Deep Learning) for natural language. My current research interest is largely focused on machine
While much of the focus in the Julia community has been on the performance aspects of Julia relative to other scientific computing languages, Julia is also perfectly suited to ‘glue’ together multiple data sources/languages. In this blog post, I will cover how to create an interactive plot using Gadfly.jl, by first preparing the data using Hadoop and Teradata Aster via ODBC.jl. The example problem
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