Practical Machine Learning in Production: Using Decision Forests

Decision Forests are widely used in data-intensive machine learning workflows where decision making must be done quickly, at high accuracy, and on streaming and large-scale data.'s implementation is built from the ground up: it extends the attributes of Decision Forests to be highly scalable to handle enterprise data volumes, extremely fast to handle real-time use cases, easily interpretable by business users and rapidly implementable into production.

In this whitepaper you'll learn more about machine learning (particularly supervised learning) and Decision Forests: what they are and how they are used throughout industry. We show how innovations like instance-level feature importances expand the explanatory power of models and predictions.

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