https://github.com/davibarreira/julia_tutorials

Collection of tutorials on Julia
https://github.com/davibarreira/julia_tutorials

julia julia-language julialang machine-learning tutorials

Last synced: about 2 months ago
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Collection of tutorials on Julia

• Host: GitHub
• URL: https://github.com/davibarreira/julia_tutorials
• Owner: davibarreira
• License: mit
• Created: 2020-10-02T15:15:17.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2024-03-18T11:10:52.000Z (9 months ago)
• Last Synced: 2024-11-01T17:42:17.434Z (about 2 months ago)
• Topics: julia, julia-language, julialang, machine-learning, tutorials
• Language: Jupyter Notebook
• Homepage:
• Size: 21.6 MB
• Stars: 8
• Watchers: 2
• Forks: 3
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Julia Tutorials

### A repository for interesting Tutorials in Julia.

Since Julia is still a "new" language, there is not as much material

out there, with easy to follow tutorials on how to do many things. Hence,

this is a personal repository to collect Tutorials in Julia,

This repository is related to the publication [Coffee in a Klein Bottle](https://medium.com/coffee-in-a-klein-bottle).

Below, the List of Contents of tutorial related to Coffee in a Klein Bottle:

* [Speeding Up Julia Precompilation](https://github.com/davibarreira/Julia_Tutorials/tree/main/Speeding_up_Julia_Precompilation) - How to use PackageCompiler.jl

to create precompiled versions of Julia with your favorite packages, and speed up the process of starting a new kernel;

* [Deep Learning with Julia](https://github.com/davibarreira/Julia_Tutorials) - A brief tutorial on training a Neural Network with Flux.jl.The notebook [here](https://github.com/davibarreira/Julia_Tutorials/blob/main/MachineLearning/Flux_Tutorial1.ipynb) corresponds to the code shown in the article;

* [Analyzing Graphs with Julia](https://medium.com/coffee-in-a-klein-bottle/analyzing-graphs-with-julia-38e26d1d2f62) - A brief tutorial on how to use Julia to analyze graphs using the JuliaGraphs packages. The notebook [here](https://github.com/davibarreira/Julia_Tutorials/blob/main/Graphs/Graphs_Tutorial.ipynb) corresponds to the code shown in the article.

## Useful External Links

* [Autoencoders tutorial with Flux](https://wildart.github.io/)