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View Code? Open in Web Editor NEWScalable Function as a Service(FaaS) for Python
License: MIT License
Scalable Function as a Service(FaaS) for Python
License: MIT License
Use the function created at #6 to generate a dataset for 1 month's worth of data. This will allow the start of parallel linear regression testing for prediction.
TODO:
_notebooks/
folder.Document how to install the kubernetes and kubeless:
Add the following diagrams:
Add the last timetick as an argument, along with polling intervals.
Add more:
We should define a better scope for this (creating a FaaS framework from scratch is overkill for a semester at university). As long as we leverage cloud environments and distributed systems it is in "my field" and I can help (I have experience with Python, AWS, Docker, and Kubernetes).
TODO:
_docs/
folderSplit data into 2d arrays, each row representing one day's worth of data.
Train any model having the date as an input.
Detail project architecture:
More to be added in the following weeks.
Wider scope datasets will use 1-day scope dataset generation.
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