Choosing a topic

[rasmushenningsson]

Below is a list of some possible topics to choose from. You are more than welcome to come up with your own. If a topic is too big, you can split it with someone else and present together or separately as you wish, maybe over two sessions.

The idea is to choose a topic that feels important for you to be able to use Julia for real work later. So if you need to parse csv and other file formats for your work, that's a good topic.

• Plotting
• Parsing various formats (csv, excel, etc.)
• Distributions
• Data Frames
• Unit testing
• Julia JIT compiler
• Present one of the Julia packages

[rasmushenningsson]

Here are some packages that could be interesting. More packages and details can be found here: http://pkg.julialang.org

• Clustering
• CSV
• Convex - convex optimization
• DataArrays
• DataFrames - R-style Data Frames
• Distributions - Many things related to statistical distributions
• ExcelReaders
• FastaIO - Read fasta files
• MAT - Reading matlab files
• MATLAB - Calling matlab
• MLBase - Machine Learning
• MixedModels
• MultivariateStats
• PValueAdjust
• PyCall
• RCall
• Stan - Interface to Stan which is a famous program for doing MCMC

[rasmushenningsson]

One topic I really want to cover is plotting. It might be too big for one person, but it should be easy to split, because there are several packages for plotting in Julia.

For instance, if someone likes ggplot2 in R, they could present the Gadfly package in Julia which is similar.

PyPlot is another package that relies on pythons matplotlib for plotting. It is probably more familiar for everyone that's not used to ggplot2. Someone else could present PyPlot.

A brief overview of the other packages for plotting would also be useful.