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Picture this: On one hand, we have a thrill-seeking adventurer, who embraces a life of adrenaline and excitement, constantly seeking new challenges to conquer. Their world is brimming with boundless energy, exploring the wilderness through activities like rock climbing, off-road biking, or bungee jumping. On the other hand, we have
Data, in itself, has many characteristics and challenges, especially in the world of big data. Those who utilize or collect data know about the hardships it brings. That’s why there are some widely known descriptions and parameters of data where certain characteristics are described for better management. One of the
As time goes on and the volume of data rises, traditional data management processes aren’t enough. It gets more complicated and time-consuming to draw out valuable data, process it, and prepare it for other data-related tasks. But, with the development of AI, we see the possibilities of augmented data management.
If you are an enterprise company or an entity that either generates or collects enormous amounts of data, then you must be familiar with the fact that the more data you have, the more you’ll add on. As soon as you recognize the value of data in your everyday operations,
With recent developments in the field of machine learning, collecting and analyzing data has become a crucial part of improving almost every industry in the world. This is why researchers from the Faculty of Education and Rehabilitation Sciences in Zagreb approached us to determine to which degree state-of-the-art machine learning
Getting into machine learning is all fine and well. And, yes, it’s something that has revolutionized businesses and started so many opportunities for better products and services. But, like with everything that brings good, there are threats to it. And in comes adversarial machine learning (AML), as a threat to
