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when you start learning and creating machine learning models you might run into a few different ways used to describe how your model is running or being used training is when you take your data and try to make your model learn how to solve your problem evaluation is when you take your data and you try to see how well your model is performing currently during evaluation you still run all your metrics you just are updating the model prediction is when you take the data and you try to get make a guess at what the solution is you dont run any metrics and you arent updating the model but instead you are just trying to take in the input and trying to predict the answer there will often be some kind of mapping that occurs here especially in classification problems where youre trying to say that greater than point five is a cat or that anything in this cluster is French you