The field of machine learning includes the development and application of computer algorithms that improve with experience. Machine learning methods can be divided into supervised, semi-supervised and ...

The chapters of “Machine Learning Methods for Engineering Application Development“ book are organized into five parts Machine Learning Essentials, Applied Machine Learning, Surveillance Systems, ...

Machine learning components are enabling advances in self-driving cars, the power grid, and robotic medicine, but what are the implications for safety? Decades of research and practice in safety ...

Machine learning is rapidly emerging as a pivotal tool in plant tissue culture research, offering innovative approaches to optimise protocols, predict morphogenic responses, and streamline ...

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Technologies grouped under big data, artificial intelligence and machine learning are impacting virtually every aspect of life today. More importantly for the U.S. military and for the companies in ...

Artificial intelligence (AI) has changed the face of modern finance, bringing the efficiency and security of intuitive decision-making to the business sector. The use of AI allows various financial ...

Now that we’re big into machine learning in the cloud, perhaps we should start thinking about how to do it better ML (machine learning) is handy stuff. Now that public cloud computing has made it ...

In this and future posts, I thought it might be useful to provide some real-world applications of machine learning in a trading context. Because machine learning is such a broad topic, I am going to ...