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Automate external data discovery and enrichment for more accurate predictive models.
Creating a rock star data science team is about so much more than tracking down the right job titles or developing the right algorithms.
Sure, you need the technical skills – or technologies – to make your projects a success. But just as importantly, your team needs to be adept at building bridges across the organization. At securing the buy-in of colleagues in all areas of business. At translating domain expertise and business challenges into machine learning models.
In this whitepaper, we cut through the noise to explain exactly which skills and roles are most vital for your data science team.
You’ll discover:
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.
This complete guide breaks down data acquisition into six steps, including data provider due diligence and data provider tests to uplift your model's accuracy.
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