Julia is a high-level dynamic language which was invented out of greed to do more. Unlike other high-level dynamic languages, Julia is really fast. It inherits design tenets from Lisp, builds on the good parts of C, MATLAB, R, Python and Ruby to create a language that is performant and highly productive at the same time.
We are proud to announce the first ever JuliaCon India. It will feature the creators of the language Jeff Bezanson, Stefan Karpinski, and Viral B Shah, and an enthusiastic contingent of Julia programmers in India. It’s a two-day event consisting of a day-long conference (9th Oct) and a workshop (10th Oct).
Julia: A Workshop
Participants of this workshop will learn about the features of the Julia language, its package ecosystem and how to build scalable real-time data-intensive applications in a series of hands-on learning sessions.
Julia is a high-level, high-performance dynamic language, it uses just-in-time compilation to provide fast machine code - dynamic code runs close to the speed of C, and orders of magnitude faster than traditional numerical computing tools.
This workshop will be divided into 4 parts:
1. Analytics and data science with Julia
2. Julia language constructs
A complete overview of the Julia language, which includes concepts such as functions, standard library, types, multiple-dispatch, macros, introspection, modules, packaging and a brief look at the language infrastructure.
3. Working with big data and parallel computing
What would you do with a thousand processors? In this session we will explore the parallel computing capabilities of Julia, integration with Hadoop file system tools for setting up data processing pipelines.
4. Pair-programming: build your own Julia application
In this session you will pair up with a teammate to build a simple application (e.g. a recommendation engine) and deploy it as an auto-scaling REST applcation on JuliaBox or locally.
Install Julia 0.3 (you can also install 0.4-rc4 alongside, but 0.3 is required for the tutorial) see http://julialang.org/downloads
Install the following packages by running Pkg.install(“<package-name>”) in the Julia REPL.
IJulia, Gadfly, PyPlot, Interact, JuMP, DataFrames - do not worry if you are having trouble installing any of these packages. We will have a server with all these installed as fallback but we want you to be prepared for a no-internet scenario.
It is recommended that if you use Windows, you install the Juno IDE