Resources for learning Julia

Keep tracking of blogs, videos, threads, issues, Q&As, quotes... (work in progress)

• official
• Julia motivation: why weren’t Numpy, Scipy, Numba, good enough?
• A Deep Introduction to Julia for Data Science and Scientific Computing
• 7 Julia Gotchas and How to Handle Them
• Using Julia's Type System For Hidden Performance Gains
• What features will I miss in Julia?
• I Like Julia Because It Scales and Is Productive: Some Insights From A Julia Developer
• Julia.jl
• Why I use Julia
• Why I’m Betting on Julia
• List of most desired features for Julia v1.x
• What can we do to make Julia grow fast?

Intro. Videos

• Jeff Bezanson & Stefan Karpinski - Julia: Numerical Applications Pushing Limits of Language Design
• Jeff Bezanson - Why is Julia fast?
• Stefan Karpinski - Julia + Python = ♥
• Stefan Karpinski - Julia: Fast Performance, Distributed Computing & Multiple Dispatch
• John Pearson | Introduction to Julia for Pythonistas
• DataScienceSG 2016 | Prof Alan Edelman | Introduction to Julia
• Josh Day | Julia for Modern Data Analysis

  David P. Sanders' Tutorials

• [JuliaCon 2017]An Invitation to Julia: Toward Version 1.0
• [JuliaCon 2016]Intermediate Level Julia
• [JuliaCon 2015]Introduction to Julia for scientific Computing
• [SciPy 2014]Introduction to Julia - Part 1
• [SciPy 2014]Introduction to Julia - Part 2