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Do You Trust and Understand Your Predictive Models?

To help practitioners make the most of recent and disruptive breakthroughs in debugging, explainability, fairness, and interpretability techniques for machine learning, our friends over at H2O.ai have written and exciting eBook “An Introduction to Machine Learning Intrepretability Second Edition.” This report defines key terms, introduces the human and commercial motivations for the techniques, and discusses predictive modeling and machine learning from an applied perspective, focusing on the common challenges of business adoption, internal model documentation, governance, validation requirements, and external regulatory mandates.

Machine learning for all: the democratizing of a technology

In this short eBook, you’ll discover automated machine learning using H2O.ai. H2O.ai has dedicated itself to democratizing all aspects of AI, including machine
learning. H2O Driverless AI is a machine learning solution that automates AI for nontechnical
users. So-called “AutoML” solutions like H2O Driverless AI are rising in popularity for enterprises across a wide range of industries. With it, users can build robust, fast, and accurate machine learning solutions. It also includes visualization and interpretability features that explain the data modeling results in plain English, fostering further adoption and trust in AI.