Deploy first ML model to predict viral moments in live streams

[gatesyp]

We want to deploy a better version of ClipFinder that is tuned to 'predicting viral moments in livestreams'.

Here is a very rough roadmap:

• Create initial dataset
• Iterate current statistical pillar_algos to experiment + try to fit model to dataset
• Create ML model that outperforms previous statistical model
• Integrate Metaflow with our AWS environment
• Deploy model to AWS

[pomkos]

re ML model: 75% used to train, 25% used to test. We will use the CCC dataset.

[pomkos]

Each CCC will be labeled as viral or not. Virality defined by @gatesyp.

Binary categorization ML model will be used to predict whether a clip will go viral or not.