Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...

This project implements a deep learning approach for anomaly detection in time-series data using a PyTorch-based Autoencoder. The model is trained to reconstruct normal data patterns and then used to ...

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...

This code implements an algorithm that predicts blood glucose levels by analyzing the intensity of different wavelengths using Raman spectroscopy. It trains a linear-scaling autoencoder (LSE) model on ...