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Step 1 of 5 · What type of data do you have?
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What type of data are you working with?
Choose the primary modality of your input data.
What is your primary task?
What outcome do you want to predict or produce?
How much labeled training data do you have?
Labels = human-annotated ground-truth examples.
How important is model interpretability?
Can you deploy a black-box model, or do stakeholders need explanations?
What is your compute / latency profile?
Affects whether large neural models are practical.
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