Turning tabular data into ‘pseudo-notes’ that mirror clinical documentation allows AI models to analyze patient information ...

In this TechRepublic exclusive, a COO states that successful AI initiatives must have the right unstructured data at the ...

Google retires seven structured data features including Book Actions, Course Info, and Claim Review to streamline search results. Rankings unaffected.

Keywords: multi-source data fusion, deep convolutional autoencoder, slope displacement, rainfall, health monitoring Citation: Han N, Miao W, Li M, Mohamad Ismail MA, Hu Q, Duan L and Tang J (2025) ...

3.1 2D convolutional autoencoder An autoencoder (AE) is a neural network model primarily used for unsupervised learning. It achieves dimensionality reduction and feature extraction by learning to ...

Many search engines rely on structured data to enhance user experiences – and this trend will likely intensify in 2025. For this reason, structured data is no longer a “nice-to-have” but an ...

The Data Science Lab Data Dimensionality Reduction Using a Neural Autoencoder with C# Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation ...

Data-driven soft sensors play an important role in practical processes and have been widely applied. They provide real-time prediction of quality variables and then guide production and improve ...

The Data Science Lab Data Anomaly Detection Using a Neural Autoencoder with C# Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that ...