30 строки
2.1 KiB
Markdown
30 строки
2.1 KiB
Markdown
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# Code
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This directory should contain all the source code for the project. Some structure (sub-directories) is provided regarding where to store your code files.
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It is recommended to maintain the three main folders as "01\_Data\_Acquisition\_and\_Understanding", "02\_Modeling", and "03\_Deployment" and follow the steps of the TDSP data science process as outlined [(link)](https://github.com/Azure/Microsoft-TDSP/blob/master/Docs/lifecycle-detail.md).
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However, if this does not work for your project such as a big data project without a model or the code is contained in a single process, you are free to restructure folders within "Code" to suit your needs, as long as you number the folders numerically according to the stages of the process to which you approach the problem, e.g. "01\_DataPrep" and "02\_Deployment" if there contains no model.
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Please delete the comments above and use this ReadMe file to describe the structure of your code.
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### Code/01\_data\_acquisition\_and\_understanding
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[comment]: # (Include brief description of what was done here.)
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### Code/02_modeling
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[comment]: # (Include brief description of what was done here.)
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### Code/03_deployment
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[comment]: # (Include brief description of what was done here.)
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[comment]: # (Coding styles of Python and R)
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[comment]: # (It is good practice to follow coding conventions to facilitate better collaboration and standardization.)
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[comment]: # (R Style guides:)
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[comment]: # (http://adv-r.had.co.nz/Style.html Hadley Wickham's advanced R programming guide is a great resource that is accessible and a good start.)
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[comment]: # (https://google.github.io/styleguide/Rguide.xml Google's R style guide is more detailed and what I would suggest we adopt.)
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[comment]: # (http://handsondatascience.com/StyleO.pdf a 24 page detailed document that covers almost everything we could ever run into.)
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[comment]: # (Additionally, there is the _lintr_ package, which runs a syntax style checker on your code. This is what later versions of RStudio use to issue warnings while editing R code.)
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[comment]: # (Python style guides:)
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[comment]: # (https://www.python.org/dev/peps/pep-0008/)
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