1. Handbook of Anomaly Detection: Cutting-edge Methods and Hands-On Code Examples
This comprehensive guide, authored by Chris Kuo, stands out as a crucial resource for anyone delving into the world of anomaly detection. The book elegantly combines theory and practical hands-on code examples, making complex algorithms approachable for readers at all levels. Set to be published on October 17, 2024, at a price of $65.00, it prepares you to tackle real-world challenges in data anomaly analysis. With a focus on up-to-date methodologies, it is undoubtedly a must-read.
2. Outlier Detection in Python
Brett Kennedy’s upcoming book provides an invaluable guide tailored for practitioners who aim to harness the power of Python in outlier detection. With a release date of January 7, 2025, priced at $58.44, it walks readers through practical implementations, enabling them to develop robust outlier detection systems. This book is perfect for both seasoned developers and newcomers eager to enhance their analytical skills using Python.
3. Anomaly Detection Principles and Algorithms (Terrorism, Security, and Computation)
This profound work authored by Mehrotra, Mohan, and Huang dives into essential principles and algorithms of anomaly detection, particularly in the realm of security and computation. Published on January 25, 2018, for $87.94, this book offers critical insights into understanding anomalous behaviors, making it suited for professionals involved in security, data analysis, and computation fields.
4. Beginning Anomaly Detection Using Python-Based Deep Learning: Implement Anomaly Detection Applications with Keras and PyTorch
Written by Suman Kalyan Adari and Sridhar Alla, this book is designed for those wishing to implement anomaly detection applications using contemporary deep learning frameworks such as Keras and PyTorch. Slated for publication on January 2, 2024, with a price of $49.41, it serves as an ideal introduction for beginners aiming to bridge theoretical concepts with practical skills in Python.
5. Modern Time Series Forecasting Techniques For Predictive Analytics and Anomaly Detection
In his latest work, Chris Kuo discusses innovative forecasting techniques for predictive analytics and anomaly detection. Priced at $65.00 and releasing on May 28, 2024, this book merges classical statistical methods with modern machine learning approaches, providing readers with actionable insights for real-time data analysis. It’s perfect for data analysts eager to enhance their predictive capabilities.
6. Deep Learning and XAI Techniques for Anomaly Detection
This insightful book by Cher Simon offers a unique perspective on deep learning and explanations in anomaly detection. Set to enrich both theoretical foundations and practical applications, this book is available for $46.99 as of January 31, 2023. It empowers readers to understand complex model behaviors and enhance anomaly detection practices, making it a valuable addition to any analyst’s library.
7. Outlier Analysis
Charu C. Aggarwal’s “Outlier Analysis” is a must-read for those specifically focused on identifying outliers within datasets. Priced at $37.88, it was published on December 22, 2016. This book addresses various approaches of outlier detection, enhancing the reader’s ability to uncover meaningful patterns hidden in noise. It’s a core reference for anyone serious about data mining.
8. Network Anomaly Detection Handbook: A Practical Guide for Securing Networks Using AI-Powered Techniques
This practical handbook, authored by Siya Sethi and Saurabh Shrivastava, is an essential read for cybersecurity enthusiasts. Offering insights into securing networks through AI techniques, it is priced affordably at $14.99 and set to publish on September 6, 2024. The handbook is an invaluable resource for professionals eager to understand network vulnerabilities and safeguard against potential threats using anomaly detection.
9. Beginning Anomaly Detection Using Python-Based Deep Learning: With Keras and PyTorch
Another collaborative effort by Suman Kalyan Adari and Sridhar Alla, this book is tailored for those who prefer hands-on learning in anomaly detection via Python. This version, priced at $44.99 and published on October 11, 2019, is densely packed with practical implementations and case studies, crucial for nurturing a functional understanding of anomaly detection techniques.
10. Finding Ghosts in Your Data: Anomaly Detection Techniques with Examples in Python
Finally, Kevin Feasel’s “Finding Ghosts in Your Data” offers a unique take on anomaly detection through guidance with Python. Published on November 10, 2022, this book, available at $34.25, focuses on practical techniques and provides examples that equip readers to effectively handle real-world data. It’s perfect for those looking to apply anomaly detection methodologies in their projects.
