Thursday, June 17, 2021
Machine Learning models are built by seeing a series of examples and using those to discover patterns that can help predict future examples. As humans we do this too. We learn what an apple is by seeing one and being told it's an apple. As these problems get more complicated so too does measuring their success and that's where models, both human and machine, can fail. We'll talk through some examples of what this means and how it works in the real world.
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