Opening up the black box: an introduction to model explainability
What is Model Explainability and how can it give you more insight into Machine Learning predictions?
We look at skills, composition, numbers, experience and just hope that the magic will happen and that teams will deliver results: both business results and people results.
What we are not sure about, is the throughput. The psychological concepts above, like psychological safety, inclusion and belonging are very well researched and have a significant impact on the throughput, on the team dynamics.
They make a good team, with the right people, at the right place, actually perform.
Based on this research, and combining our experience in science, machine learning and data-science, we built JiGSO Listen. Giving teams the insights and the tools to start working with that. Not just hoping for the magic, but start building the magic.
Or as Siska D’Hoore, HR-director of the National Bank of Belgium said:
Our employees must dare to question existing situations in order to make changes possible. They must not be afraid to express new ideas. To analyse this safety situation in our own teams, we used Jigso Listen
With JiGSO Listen, we give the insights and the tools to the teams themselves.
The web-based platform guides teams through a three-step learning loop:
What is Model Explainability and how can it give you more insight into Machine Learning predictions?
Censoring is an important feature in Survival Analysis that helps you take into account missing data.
Introducing the concept of Survival Analysis and how it can help you understand churn.
Short explainer video introducing JiGSO Listen and how this smart platform can help your teams thrive and your organisation triumph.