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Automate external data discovery and enrichment for more accurate predictive models.
Data scientists are constantly challenged with improving their ML models.
But when a new algorithm won’t improve your AUC there’s only one place to look: DATA.
Generating, testing, and integrating new features from various internal and/or external sources is time-consuming, difficult, and more “artistic.” But it could lead to a major discovery and move the needle much more.
This whitepaper breaks down:
Automate external data discovery and enrichment for more accurate predictive models.
It's time to take feature generation - a subset of feature engineering - from an art to a science by opening up additional data sources to achieve breakthroughs in predictive models.
Why are we still hung up on BI? It’s time to embrace a paradigm that empowers us to make smarter, better predictions using real data with machine learning.
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