Re-posted from: http://www.youtube.com/watch?v=1iBLaHGL1AM&feature=youtube_gdata
Julia provides a built-in interface to the FFTW (http://www.fftw.org/) library. This session demonstrates the Julia’s signal processing (http://docs.julialang.org/en/release-0.1/stdlib/base/#signal-processing) capabilities, such as FFTs and DCTs. Also see the Hadamard (https://github.com/stevengj/Hadamard.jl) package.
Re-posted from: http://www.youtube.com/watch?v=JoRn4ryMclc&feature=youtube_gdata
Parallel and distributed computing (http://docs.julialang.org/en/release-0.1/manual/parallel-computing/) have been an integral part of Julia’s capabilities from an early stage. This session describes existing basic capabilities, which can be used as building blocks for higher level parallel libraries.
Lab: https://github.com/JuliaLang/julia-tutorial/raw/master/NumericalOptimization/tutorial.pdf
Solution: https://github.com/JuliaLang/julia-tutorial/blob/master/NumericalOptimization/Tutorial.jl
Re-posted from: http://www.youtube.com/watch?v=XRClA5YLiIc&feature=youtube_gdata
DataFrames (https://github.com/HarlanH/DataFrames.jl) is one of the most widely used Julia packages. This session is an introduction to data analysis with Julia using DataFrames.
Slides: https://github.com/JuliaLang/julia-tutorial/raw/master/DataFrames/slides.pdf