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I'm planning an example requested by @phmalek about machine learning. I am using a data structure for my current research that has multiple projects, with one project for data (which doesn't really change) and one project for different models and their hyperparameters (which is where most of the "operations" happen). I am looking for toy examples of hyperparameter optimization to demonstrate this structure. I may find some good examples that can be adapted from packages like hyperopt.
Original report by Carl Simon Adorf (Bitbucket: csadorf, GitHub: csadorf).
The example should demonstrate how to integrate multiple projects either directly or via an index.
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