How humans cause bias in machine learning, how marketers can improve personalization, and why some problems might not be solvable.
- By Upside Staff
- January 15, 2019
Improving predictive analytics, the dangers of customer unfriendly AI, and new medical uses for machine learning.
- By Upside Staff
- January 10, 2019
To get the greatest value out of your organization’s data, your data science team needs to play five distinct roles: innovators, explorers, prototypers, optimizers, and responders.
- By Troy Hiltbrand
- January 9, 2019
These inventive visualizations compare the types of life on earth, simulate population growth, and explore the impact of celebrities’ deaths.
- By Upside Staff
- January 9, 2019
Widen BI adoption and use with these steps that won't disrupt your environment.
- By Lyndsay Wise
- January 8, 2019
We explore what deep learning is and the benefits it offers, its relationship with AI, and where it’s headed with Martin Ford.
- By James E. Powell
- January 2, 2019
Using data to estimate Santa’s speed, exploring how the U.S. celebrates Christmas, and when people get tired of Christmas music.
- By Upside Staff
- December 19, 2018
Moving to a hybrid cloud analytics model can help you remove analytics roadblocks, but today's new data environment can introduce new problems because it is so complex. Being aware of these issues is the first step to overcoming them.
- By James E. Powell
- December 14, 2018