Unplanned downtime costs can cripple the best-laid production and financial plans. Smart businesses have turned to ML for help. Mining and merging historical, contemporary data, ML algorithms lay out patters that best predict when a product, machinery is most likely to give way. This is a boon for manufacturers, retailers as they can enjoy the luxury of just-in-time inventory.
Maintenance costs are inversely proportional to time – shorter the time, higher the costs. ML can give the much needed window of time
In service sector downtimes can cause customer and, revenue loss Experts have turned to ML to reduce machinery downtime.
Studies have showed that the best production floors operate on predictive and prescriptive modes. ML makes that possible.
Component fatigue is among the least understood and most worrisome issue that aviation industry faces. ML gives insights.
When it comes to scope the wheel turns a full 360-degrees for Machine Learning. From customer retention to fraud detection, different businesses have turned to ML to address problems that have bugged their bottom-lines. Aim It ML practice has ML solutions for businesses as diverse as banking , manufacturing and, telecom
In these uncertain times when markets tend to expand and shrink in quarters, it is important the deep-learning based prediction models guide your investment decisons.
Enormously capital-intensive and extremely volatile, flash-trading is seen as a high risk option by all, but a few of the big banks. Instead try out our much safer ML-based price platform.
As automation and e-commerce have both become norms, prevention and minimizing of payment fraud has become a priority task for risk and, compliance teams. It’s no small wonder that banks, e-commerce firms are among the early adopters of ML.
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