rTorch, a minimal book

26 October 2020
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A Minimal Book for rTorch

Why do we want a package of something that is already working well, such as PyTorch?

There are several reasons, but the main one is to bring another machine learning framework to R. Probably, it is just me but I feel PyTorch very comfortable to work with. Feels pretty much like everything else in Python. Very pythonic. I have tried other frameworks in R. The closest that matches a natural language like PyTorch, is MXnet. Unfortunately, MXnet it is the hardest to install and maintain after updates.

Yes. I could have worked directly with PyTorch in a native Python environment, such as Jupyter, or PyCharm, or vscode notebooks but it very hard to quit RMarkdown once you get used to it. It is the real thing in regards to literate programming and reproducibility. It does not only contribute to improving the quality of the code but establishes a workflow for a better understanding of a subject by your intended readers, in what is been called the literate programming paradigm.

This has the additional benefit of giving the ability to write combination of Python and R code together in the same document. There will be times when it is better to create a class in Python; and other times where R will be more convenient to handle a data structure. I show some examples using data.frame and data.table along with PyTorch tensors.

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