Fall in love with Julia: Statistics & co with JuliaStats & StatsKit.jl

Hi all, this introductory series is for you:

• you do Data Science in R, Python, Matlab, Fortran, etc.?
• you like it high-level and high-performant?

Statistics is at the heart of Data Science. The JuliaStats organisation with their StatsKit.jl meta-package enable you to run standard statistical analysis with high-performance in Julia.

We are going to take a tour through the JuliaStats ecosystem, looking at metrics, distributions, distances, bootstraps, hypothesis tests and more.

As usual in this series, you will get a beginner-friendly hands-on experience using a Jupyter-Notebook, with which you can try out StatsKit.jl yourself and also experiment further afterwards. The material will be made available at the github repository https://github.com/schlichtanders/fall-in-love-with-julia
You do not need to prepare anything.

Looking forward to see you all!
Spread the news and invite everyone to this Julia 101!
It is going to be online, so everyone from everywhere is welcome.

yours,
Stephan Sahm
Founder of Jolin.io consultancy
www.jolin.io

JuliaPerformance is currently being rebranded to Jolin.io.

P.S.: The link to the online tool will be made available 10 min before the actual start. Please join 5 min ahead, the session is going to start on-time, 18:30 CET.