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...As an example, the function func above is available in Julia as c"func". It is possible to store the generated bindings to more user-friendly names (this can sometimes be automated, see the j option). Placing each C declaration in its own macro helps when doing this manually.

...The main purpose is to facilitate writing Julia examples/tutorials that can be included in your package documentation. Literate can generate markdown pages (for e.g. Documenter.jl), and Jupyter notebooks, from the same source file. There is also an option to "clean" the source from all metadata, and produce a pure Julia script. Using a single source file for multiple purposes reduces maintenance, and makes sure your different output formats are synced with each other.

The Beta Machine Learning Toolkit is a package including many algorithms and utilities to implement machine learning workflows in Julia, Python, R and any other language with a Julia binding. All models are implemented entirely in Julia and are hosted in the repository itself (i.e. they are not wrapper to third-party models). If your favorite option or model is missing, you can try to implement it yourself and open a pull request to share it (see the section Contribute below) or request its implementation. Thanks to its JIT compiler, Julia is indeed in the sweet spot where we can easily write models in a high-level language and still have them running efficiently.

2D plotting for Julia. Winston offers an easy-to-use plot command to create figures without any fuss. After Winston is loaded by typing using Winston, the most basic plot can be created.

This package has been merged into the Julia standard library. As such, you probably just want to using REPL.TerminalMenus and skip the Installation instructions. The RadioMenu allows the user to select one option from the list. The request function displays the interactive menu and returns the index of the selected choice. If a user presses 'q' or ctrl-c, request will return a -1.