Julia Workshop Materials

A module capturing a series of notebooks and scripts presenting Julia's capabilities.

To install, execute in Julia REPL (if it does not work follow all the steps under Julia and GIT below):

	ENV["PYTHON"] = ""
	import Pkg
	Pkg.add(url="https://gitlab.lanl.gov/julialang/juliaworkshop.jl", rev="master")

The official Julia documentation is available at https://docs.julialang.org.

The official Julia discourse https://discourse.julialang.org is an excellent resource for all kinds of questions and insights in addition to Stack Overflow.

In the Julia community, it is not recommended to push/pull requests, submit coding issues, or ask questions before you have checked for existing answers or insights at the Julia discourse website.

Contents

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The JuliaWorkshop module showcases how to code and perform machine-learning analyses in Julia.

The JuliaWorkshop module covers various topics which are organized into a series of Jupyter and Pluto notebooks:

• Functional programming
• Parallelization
• GPU acceleration
• Machine Learning

Specifically related to Machine Learning, we will cover a series of general, frequently-solved ML tasks such as:

• Classification
• Regression
• Blind source separation
• Feature extraction
• Anomaly Detection
• Spatiotemporal data analytics
• Filling data gaps

We will also present a series of real world ML examples related to:

• Jupiter red spot
• CO2 monitoring
• GeoThermal exploration
• Turbulence
• Europe Climate
• California Wildfires
• Contaminant transport (i.e., water unmixing)

Notebooks

The JuliaWorkshop notebooks can be executed in Jupyter or in the Julia REPL.

For example, the Parallelization notebook can be accessed using:

	JuliaWorkshop.notebook("Parallelization")

The Parallelization notebook can also be executed as a Julia script in the Julia REPL using:

	JuliaWorkshop.notebookscript("Parallelization")

The script above generates a Julia file named Parallelization.jl which can be executed in the Julia REPL.

The Parallelization notebook can be processed to generate html, markdown, latex, and script versions using:

	JuliaWorkshop.process_notebook("Parallelization")

To access all the workshop notebooks, execute:

	JuliaWorkshop.notebooks()

Getting Started

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Download and install the latest version of Julia.

Alternatively, you can use the Julia version manager JuliaUp. This recommended way to manage julia upgrades.

Using tools such as apt-get, brew or mac-ports is not recommended.

Julia REPL

Julia REPL looks like this:

Julia and GIT

Julia uses GIT for package management. GIT needs to be installed and configured as well.

JuliaWorkshop materials

You can install JuliaWorkshop module:

	ENV["PYTHON"] = ""
	import Pkg
	Pkg.add(url="https://github.com/SmartTensors/JuliaWorkshop.jl", rev="master")

Jupyter Notebooks

Jupyter notebooks are in-browser interactive programming environments that we will use for this workshop. The notebooks are run through IJulia.

To access the JuliaWorkshop notebooks, execute:

	JuliaWorkshop.notebooks()

When JuliaWorkshop is installed, it also installs IJulia.

To install IJulia separately, open a Julia REPL and run:

	ENV["PYTHON"] = ""
	import Pkg
	Pkg.add("IJulia")

To open a Jupyter Notebook session in your browser, run the following in a REPL:

	import IJulia
	IJulia.notebook()

The first time you run this, it will install jupyter using conda.