ML Tag

By now, the positive impact of digitalization in manufacturing environments is widely recognized — reduced costs, improved operational efficiency and greater productivity. But digitalization is not fulfilled by making just a single change. It is a continuous cycle of updates

Knowing how to manage and process data, information, is an asset of the digital enterprise. That's why analytics tools are becoming increasingly important in the manufacturing sector. As highlighted by Gartner in one of its Magic Quadrant for Analytics and Business

Artificial intelligence does not have an unambiguously accepted definition. This is because AI is not a stand-alone technology but a combination of different technologies that, properly orchestrated with each other, allow machines to act, almost, autonomously. Unlike automation, AI doesn't

What is Ensemble Modeling? Ensemble Modeling is a technique used to improve the results of Machine Learning projects. This Ensemble Modeling technique allows to obtain a better predictive performance compared to the models from which it is made up, thanks to

Machine Learning is a subset of artificial intelligence (AI) that deals with creating systems that learn or improve performance based on the data they use: it has unprecedented computational capacity, but on its own it cannot be perfect. It always requires

We live in a world of increasingly smart and interconnected devices. From power grids to industrial control systems and vehicle fleets, IIoT devices are proliferating. Recent estimates project that there will be well over 24 billion IoT devices within the

Artificial Intelligence, or AI, isn’t actually a new concept. In fact, it’s been around since the 1950s. The problem back then was that computers lacked the ability to store commands, so they could be told what to do but couldn’t

Artificial Intelligence (AI) and Machine Learning (ML), are huge contributors in these advances and have revolutionized the way that software operates and functions for the manufacturing industry. AI and Machine Learning in ERP Systems Artificial Intelligence and Machine Learning have drastically enhanced

According to Gartner, 85% of Machine Learning (ML) projects fail. Worse yet, the research company predicts that this trend will continue through 2022. Does this point to some weakness in ML itself? No, it points to weaknesses in the way