# Machine Learning Project Workflow Collect > Train > Deploy - Collect data: examples of input to output - Train a model that learns how to map inputs to outputs - Iterate until the model becomes "good enough" - Deploy the model so it can be used - Get more data, maintain and update the model ## Related - [[CRISP-ML(Q)]] (a detailed, quality-assured version of this workflow)