Refined and labeled data is imperative for advances in AI. When your supply of good data does not match your demand, look to synthetic data to fill the gap.
- By Troy Hiltbrand
- November 22, 2019
Garbage training data in, garbage model out. Here are four things to address to solve data quality problems.
- By Brian J. Dooley
- November 21, 2019
Building a great machine learning team, removing data silos, and managing the structure of data governance organizations.
- By Upside Staff
- November 21, 2019
These articles explain current data regulations, trends in online fraud, and the challenging state of privacy policies.
- By Upside Staff
- November 20, 2019
Focusing on business outcomes, aligning teams, and achieving quick wins can help your AI analytics program succeed.
- By Pete Reilly
- November 18, 2019
New data sources and the spread of real-time data analysis are leading to increased interest in optimizing human and electronic processes.
- By Brian J. Dooley
- November 15, 2019
How to do personalization right, protect loyalty programs, and drive e-commerce with data science.
- By Upside Staff
- November 14, 2019
These charts use data to shed new light on medical research, vaccine history, and opioid use.
- By Upside Staff
- November 13, 2019