The Power Of Automation: The Role Of Machine Learning In Cybersecurity ForbesEvery CISO is acutely aware of the double-edged sword presented by the use of AI technologies such as machine learning: They are increasingly being …
How To Develop Successful Machine Learning Projects On A Budget ForbesHere’s how to develop an internally facing machine-learning model with a budget of $250000.
PredictHQ meshes event data with machine learning to help airlines forecast demand VentureBeatBig data has emerged as a lucrative by-product of the digital revolution, enabled by vast banks of information collated from the likes of smartphon…
Is machine learning and artificial intelligence a force multiplier? (sponsored) – DN – Defence Notes Shephard MediaL3Harris’ Stuart Gardiner explores how these techniques can be used in modern warfare to counter adversaries who will use ever…
What Happens When Machine Learning Finance Models Fail Spend MattersIf we are in a liquidity trap and negative interest rate environment, what does that do to the invoice finance models built with AI and machine learning?
How American Express uses machine learning to detect fraud American BankerTina Eide, Amex’s senior vice president of global fraud, discusses the card issuer’s efforts to strengthen its transaction monitoring.
The role of machine learning in a new era of asymmetric warfare (sponsored) – DN – Defence Notes Shephard MediaWhat benefit does machine learning give us in the battlespace? How can we use it ethically to make the right decisions? Is the hum…
Machine Learning, Text Analytics Aid in Food Safety at FDA GovernmentCIO MediaThe emerging technologies can predict, anticipate and protect against dangerous chemicals in the U.S. food supply.
Assessing China’s machine learning platforms ComputerWeekly.comIn a new market research report, technology analyst firm IDC offers insights on key suppliers of machine learning platforms in China.
Machine learning approach looks to reduce MRI scan times, costs Health Data ManagementResearchers contend that MRI can be accelerated through a compressed sensing approach that uses an unsupervised end-to-end learning framework.
