An Introduction to Machine Learning Interpretability
Improve the accuracy (and interpretability) of your predictive models
Between competition, innovation, and new use cases, predictive modeling and machine learning algorithms are becoming increasingly complex. This complexity makes these models accurate but can also make their predictions difficult to understand. When accuracy outpaces interpretability, human trust suffers, affecting business adoption, model validation efforts, and regulatory oversight.
An Introduction to Machine Learning Interpretability provides cutting-edge interpretability techniques. And it's yours free today.
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