[CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".
GRASPED: A GRU-AE Network based Multi-perspective Business Process Anomaly Detection Model
Simple machine learning framework for Timeseries application to identify anomaly in dataset using Machine learning and Deep neural network
Amazon product analytics: custom Pressure × Traction scoring, quadrant segmentation, sentiment analysis (VADER + TextBlob), anomaly detection, and interactive Plotly dashboard. Kaggle & Colab ready.
Add a description, image, and links to the anomaly-detectionn topic page so that developers can more easily learn about it.
To associate your repository with the anomaly-detectionn topic, visit your repo's landing page and select "manage topics."