A machine-learning model probes the relationship between a wine’s consumer rating and its chemical profile. The work provides ...

Training a machine learning model might sound tricky at first, but it’s actually pretty doable when you break it into steps. Whether you’re working with customer info, photos, or trying ...

More information: Xinwei Su et al, Machine learning modeling assisted intelligent process analysis for high - performance virus filtration, Journal of Membrane Science (2025). DOI: 10.1016/j ...

A machine learning model is the product of training a machine learning algorithm with training data. In other words, it is the result of a machine learning training process.

In today’s fast-paced analytics development environments, data scientists are often tasked with far more than building a machine learning model and deploying it into production. Now they’re ...

Automated machine learning (autoML) is the process of applying tools to data to apply the machine learning process to a real-world problem. Applying machine learning to a new dataset is a ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

In recent years, the transformer model has become one of the main highlights of advances in deep learning and deep neural networks. It is mainly used for advanced applications in natural language ...

Biases in data can be amplified by the training process, leading to distorted — or even unjust — results. And even when a model does work, it’s not always clear why. (Deep learning algorithms are ...

Two AI models. The team used two AI models—an isolation model to detect anomalies during the batch phase of the process and a random forest model to predict required operator control actions ...