ML Pipeline Logging and Inferencing Example

[kordless]

This issue replaces #14, #10, #4 and #8.

A large amount of data is desired for ingestion. Evaluate datasets which may lead to:

1. Choosing a dataset on Kaggle that has a large number amount of training data.
2. Choosing a set of models from HuggingFace that can be run on the data set, for initial labeling.
3. Building a Jupyter notebook that uses the labeled data + reports from FB to train a new model.
4. Logging the training of the new model.
5. Add a cron triggered process that does rollups.

Query exploration is desired for reporting by the user in a simple UI. This feature requires the ability of #2 for graphing the results.

[kordless]

Also replaces #14