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Outlier Detection in Python.
- Format:
- Book
- Author/Creator:
- Kennedy, Brett.
- Language:
- English
- Subjects (All):
- Outliers (Statistics).
- Anomaly detection (Computer security).
- Physical Description:
- 1 online resource (497 pages)
- Edition:
- 1st ed.
- Place of Publication:
- New York : Manning Publications Co. LLC, 2025.
- Summary:
- This book provides a comprehensive guide to outlier detection using Python, targeting professionals and researchers in data science and machine learning. It covers foundational concepts, techniques, and trends in outlier detection, including statistical methods, machine learning algorithms, and deep learning approaches. The text explores tools like scikit-learn, PyOD, and various libraries, offering practical insights for handling numeric, categorical, and time-series data. The author emphasizes workflow design, data preprocessing, model evaluation, and ensemble methods to enhance detection accuracy. The book is designed to equip readers with the skills to detect anomalies across diverse domains, such as finance, healthcare, network security, and self-driving vehicles. It is suitable for both beginners and experienced practitioners aiming to improve their anomaly detection systems. Generated by AI.
- Contents:
- Outlier Detection in Python
- Copyright
- contents
- front matter
- preface
- acknowledgments
- about this book
- Who should read this book
- How this book is organized: A road map
- About the code
- liveBook discussion forum
- about the author
- about the cover illustration
- Part 1.
- 1 Introducing outlier detection
- 1.1 Why do outlier detection?
- 1.1.1 Financial fraud
- 1.1.2 Credit card fraud
- 1.1.3 Network security
- 1.1.4 Detecting bots on social media
- 1.1.5 Industrial processes
- 1.1.6 Self-driving vehicles
- 1.1.7 Healthcare
- 1.1.8 Astronomy
- 1.1.9 Data quality
- 1.1.10 Evaluating segmentation
- 1.2 Outlier detection’s place in machine learning
- 1.3 Outlier detection in tabular data
- 1.4 Definitions of outliers
- 1.5 Trends in outlier detection Generated by AI.
- Notes:
- Description based on publisher supplied metadata and other sources.
- Part of the metadata in this record was created by AI, based on the text of the resource.
- ISBN:
- 9781638356721
- 1638356726
- OCLC:
- 1481792367
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