An Introduction to Machine Learning Interpretability

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About the Paper

Understanding and trusting models and their results is a hallmark of good science. However, today, the trade-off between the accuracy and interpretability of predictive models has been broken. But, tools now exist to build accurate and sophisticated modeling systems based on heterogeneous data and machine learning algorithms and to enable human understanding and trust in these complex systems.

Download this new O'Reilly eBook, An Introduction to Machine Learning Interpretability, to learn to make the most of recent and disruptive breakthroughs in debugging, explainability, fairness, and interpretability techniques for machine learning.

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Data Education for Business and IT Professionals

An Introduction to Machine Learning Interpretability

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About the Paper