This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
If AI systems produce biased outcomes, companies may face legal consequences, even if they don't fully understand how the algorithms work. It cant be overstated that the inability to explainAI decisions can also erode customer trust and regulatory confidence. VisualizingAI decision-making helps build trust with stakeholders.
Notably, Cognos can automatically classify data types, identifying whether columns represent measures, geographic data or plain text, then tag them with relevant icons for improved visualization. AI-powered data discovery: Cognos Analytics helps users uncover relationships and patterns that might go unnoticed in traditional BI tools.
DataRobot enables the user to easily combine multiple datasets into a single training dataset for AI modeling. In this example, the training dataset only includes information that was known before Hurricane Harvey hit the Gulf Coast to provide proactive predictions about which structures were most vulnerable.
This usually involved gathering market and property information, socio-economic data about a city on a zip code level and information regarding access to amenities (e.g., Datarobot enables users to easily combine multiple datasets into a single training dataset for AI modeling. Property performance. Property features.
We organize all of the trending information in your field so you don't have to. Join 15,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content