In order to run successful machine learning projects, and create highly-accurate predictive models for your business, you need effective data preparation. Although machine learning automation provides safeguards to prevent common mistakes, you’ll still want to correctly prepare, shape and format your data to generate optimal models.
In this on-demand webinar, Jen Underwood, Founder of Impact Analytix reviews how to organize data in a machine learning-friendly format that accurately reflects the business process and outcomes. She shares basic guidelines, practical tips and additional resources to help get you started mastering the essence of predictive model data preparation.
Discover the secrets to model-building success related to:
- Data collection and granularity
- Data formats and structure
- Analytical feature engineering
- Dealing with data quality issues