The development process for machine learning and artificial intelligence projects is quite acyclic. Model and AI Application development can always be enhanced by more visualization and exploration. However, we also need to get the project done. What is the best balance of visual exploration and application release? There are models that are commonly used during model development that enhance our understanding of which features have the greatest impact. These models may not be the best models for predictions, but this does not mean that they cannot be used for explanation. Furthermore, there are techniques that can be used to show feature significance within the model chosen for use and production. Thom will discuss these approaches and explain their application.

Thom Ives is lead data scientist for UL prospector and has the honor of serving with people that have developed a SAAS for the largest and most accurate plastics, paints, coatings, personal care and cosmetics database in the world. He is their lead and only artisan data scientist.

He also founded, owns, and leads Integrated Machine Learning & AI, which is a group of data scientists creating helpful educational content for new and existing data specialists.

Thom is married, has 9 kids = 4 bios + 5 internationally adopted. He lives in Eagle, Idaho, USA.