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Stop Explaining Black-Box Machine Learning Models For High Stakes Decisions And Use Interpretable…
Jan. 5, 2022, 2:25 p.m. | Roc Reguant
Towards Data Science - Medium towardsdatascience.com
Interpretability in machine learning
Stop Explaining Black-Box Machine Learning Models For High Stakes Decisions And Use Interpretable Models Instead
Understand the differences between pre and post model interpretation
Deep learning models are usually regarded as black boxes. That is because they are not transparent about the way they reach the prediction. Humans cannot directly interpret the model with millions of parameters. Choosing ignorance can lead to unforeseen dangers. This is inherently a bad practice that should be minimized as much …
interpretability learning machine machine learning machine learning models
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