In order to run successful machine learning projects and create highly-accurate predictive models for your business, you need effective data preparation. Although automated machine learning provides safeguards to prevent common mistakes, you'll still want to correctly prepare, shape and format your data to generate optimal models.
In this 45-minute session, Jen Underwood, Founder of Impact Analytix, will review how to organize data in a machine learning-friendly format that accurately reflects the business process and outcomes. We will share basic guidelines, practical tips and additional resources to help you start mastering the essence of predictive model data preparation. Discover the secrets to model-building success related to:
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Data collection, granularity, formats and structure
