Machine Learning Times
EXCLUSIVE HIGHLIGHTS
AI Business Value Is Not an Oxymoron: How Predictive AI Delivers Real ROI for Enterprises
  Originally published in AI Realized Now “Shouldn’t a great...
How To Un-Botch Predictive AI: Business Metrics
  Originally published in Forbes Predictive AI offers tremendous potential...
2 More Ways To Hybridize Predictive AI And Generative AI
  Originally published in Forbes Predictive AI and generative AI...
How To Overcome Predictive AI’s Everyday Failure
  Originally published in Forbes Executives know the importance of predictive...

Industry News

Applications of Predictive Modeling in Drug Development

 Recently, various empirical and semi-empirical models embedded in different modeling tools have been developed and recognized for their role in predicting pharmacokinetics of drugs in humans. These models have also been used to evaluate the effects of intrinsic (e.g., organ dysfunction, age, genetics) and extrinsic (e.g., drug-drug interactions) factors, alone or in combinations, on drug

Proactively fighting fraud with data

 A recent SAP survey found that 41 percent of financial services organization felt that predictive analytics are more about minimizing risk than exploiting opportunities. The way that statistic is phrased, it sounds like the financial industry views...

The Future of Customer Service: Predictive, Personalized

 The future of customer service is scary and rewarding at the same time. It’s scary because the machine will know everything about you. It’s rewarding because shopping will become much easier as the machine makes more decisions...

Why Predictive Analytics Marketplaces are not taking off, and how to fix it

 Three main hurdles holding back Predictive Analytics Marketplaces are a highly fragmented data mining tools market, limited support for customization, and lack of commitment. We examine how to overcome them. An earlier article on KDnuggets noted that...

Breakthrough: How to Avert Analytics’ Most Treacherous Pitfall

 This article will make you feel better. And you do need to feel better, if you are one of the many of us who practice analytics—or who must consume and rely on analytics—and find ourselves carrying tension...

Eric Siegel: An interview by Bob Morris

 Eric Siegel, PhD, founder of Predictive Analytics World and Text Analytics World, and Executive Editor of the Predictive Analytics Times.com, makes the how and why of predictive analytics understandable and captivating. In addition to being the author...

Predictive Analytics: Going beyond gut feeling in the search for new customers

 In the never-ending quest for pre-qualified leads, increasing numbers of insurance companies are turning to predictive analytics to net potential customers from that great sea of people known as the general population. Popularized in the 2011 movie,...

Data Mining Group Updates PMML

 Version 4.2 of the Predictive Model Markup Language (PMML), which aims to make it easier to develop predictive analytics apps, is now available. The Data Mining Group, a vendor-led consortium of companies and organizations developing standards for...

How bad data can lead to good decisions (sometimes)

 Before companies can profit from big data, they often must deal with bad data. There may indeed be gold in the mountains of information that firms collect today, but there also are stores of contaminated or “noisy”...

Machine Learning and Predictive Analytics Foster Growth

 Machine learning technology, which is defined in this ProgrammableWeb article, is starting to become a common component in many types of technology platforms. Machine learning has led to the advent of predictive analytics, which has been rapidly...

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