Corinium

JUNE 6, 2019

It is also important to have a strong test and learn culture to encourage rapid experimentation. What do you recommend to organizations to harness this but also show a solid ROI? What are you most looking forward to about CDAOI Insurance 2019? What is the most common mistake people make around data? It is fast and slow.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

O'Reilly on Data

MARCH 31, 2020

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. What delivers the greatest ROI? How do you select what to work on?

Management 332

Management Machine Learning Experimentation Metrics 332

Decision Management Solutions

JUNE 25, 2019

Her presentation really showed the importance of persistence, experimentation and lateral thinking in developing an analytic solution. The post Predictive Analytics World 2019 – What I Learned and What I Said appeared first on Decision Management Solutions. Details will appear at [link].

Predictive Analytics 75

Predictive Analytics Analytics Data Science Experimentation 75

Domino Data Lab

FEBRUARY 4, 2019

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Given the two points above, that’s okay—there are good ways to direct data exploration toward ROI. ethics in AI.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Corinium

APRIL 25, 2019

What do you recommend to organizations to harness this but also show a solid ROI? Whether eventual legislation will exactly mirror GDPR remains to be seen, I think there will be some experimentation at the State level as well as for specific verticals whose successes would point the way.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Domino Data Lab

MAY 8, 2019

So much work in machine learning – either on the academic side which is focused on publishing papers or the industry side which is focused on ROI – tends to emphasize: How much predictive power (precision, recall) does the model have? Jupyter Book: Interactive books running in the cloud ” by Chris Holdgraf (2019-03-27).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105