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This book is a practical guide to spotting the parts of a dataset that deviate from the norm, even when they're hidden or intertwined among the expected data points. Brett Kennedy explains how outlier ...

Development and Validation of a Machine Learning Approach Leveraging Real-World Clinical Narratives as a Predictor of Survival in Advanced Cancer Artificial intelligence (AI) models for medical image ...

Anomaly detection is the process of identifying data points, entities or events that fall outside the normal range. An anomaly is anything that deviates from what is standard or expected. Humans and ...

Commonly used outlier detection approaches, such as parts average testing or determining whether a die is good based upon other dies in the immediate neighborhood, are falling short in advanced ...

This comprehensive tutorial provides a step by step guide to performing exploratory data analysis on complex datasets using Python Pandas, Seaborn, and Matplotlib. Learn how to inspect data structures ...