Avoid 3 Common Predictive Modeling Fails – and Their Consequences

Avoid 3 Common Predictive Modeling Fails – and Their Consequences

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Data science projects can provide immense business value, but the right tools and predictive models must be in place. Large-scale data science fails, like last year’s failure to predict the winner of the U.S. presidential election, can make your organization appear faulty to those who rely on your data the most.

By taking our BI & Analytics survey, you’ll gain access to our expert guide about 3 flaws crippling data science projects.

Answer our curated questions to also discover:
•    Skills needed for data science projects
•    Strategies used by companies like Cisco to advance analytic skills
•    And more

Vendor:
TechTarget
Posted:
02 May 2017
Published:
02 May 2017
Format:
HTML
Type:
Resource
Language:
English
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