Compared to other regression techniques, a well-tuned neural network regression system can produce the most accurate prediction model, says Dr. James McCaffrey of Microsoft Research in presenting this ...

Artificial neural networks (ANNs) have found increasing usage in regression problems because of their ability to map complex nonlinear relationships. In recent years, ANN regression model applications ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

Soft sensors, also known as virtual sensors, are software that can process hundreds of measurements in combination. Plant managers who want to add soft sensors may be overwhelmed by the scope of ...

David Beer’s book The Tensions of Algorithmic Thinking has recently been published by Bristol University Press. In 1956, during a year-long trip to London and in his early 20s, the mathematician and ...

The goal of a machine learning regression problem is to predict a single numeric value. Quantile regression is a variation where you are concerned with under-prediction or over-prediction. I'll phrase ...