Enabling the AI-Driven Enterprise

How To Avoid Building Bad Models

Don’t be naive when it comes to automated machine learning. Despite the unprecedented speed and ease of creating automated predictive models today, the human mind is still essential for generating good models.

 

From selecting the right problem to solve to preventing algorithm bias, machine learning is still an art and a science. To reap the benefits of automated machine learning, Jen Underwood, Founder of Impact Analytix, will share the most common mistakes – and battle-proven practices –  to help you build better models.

On this webinar hosted by DataRobot, you'll learn the secrets to model-building success related to:

  • Selecting the right problem
  • Providing adequate data
  • Properly preparing data
  • Preventing algorithm bias

Speakers

Jen Underwood
Founder, Impact Analytix