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A Machine-Learning Approach to Phishing Detection and Defense

Approach to Phishing Detetion and Defense have conducted research to demonstrate how a machine learning algorithm can be used as an effective;

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Phishing Website Detection Using Machine Learning Algorithms

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Hands-On Artificial Intelligence for Cybersecurity

Build smart cybersecurity systems with the power of machine learning and deep learning to protect your corporate assets Key Features;

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Classification of Malware

unknown complex malware. In this work, a new approach to detect malware, which uses reverse engineering and machine learning techniques;

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Spear Phishing Attack Detection

demonstrates a strong tendency to focus its detection on new malware, which is a rare and desirable trait. Finally, after less than 4 minutes;

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Beginning Anomaly Detection Using Python-Based Deep Learning

of methods to approach anomaly detection, ranging from traditional methods to deep learning. Additionally, you are introduced to Scikit-Learn and are;

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Online and Adaptive Signature Learning for Intrusion Detection

This thesis presents the case of dynamically and adaptively learning signatures for network intrusion detection using genetic based machine;

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Machine Learning Applications for Accounting Disclosure and Fraud Detection

Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies;

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Conformal Prediction for Reliable Machine Learning

of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change;

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Network Anomaly Detection

detection system. It offers a thorough introduction to the state of the art in network anomaly detection using machine learning approaches and;

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Machine Learning with the Elastic Stack

create anomaly detection jobs and view results from Kibana directly. What you will learn Install the Elastic Stack to use machine learning;

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Hybrid Machine Intelligence for Medical Image Analysis

The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces;

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Apache Spark Machine Learning Blueprints

to build a recommendation engine using Spark's parallel computing powers. Style and approach This book offers a step-by-step approach;

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Ensemble Machine Learning Cookbook

machine learning algorithms using a recipe-based approach Implement boosting, bagging, and stacking ensemble methods to improve machine learning;

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Machine Learning Deep Learning and Computational Intelligence for Wireless Comm

This book is a collection of best selected research papers presented at the Conference on Machine Learning, Deep Learning and Computational;

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Emerging Technologies for Healthcare - Internet of Things and Deep Learning Models

them to disease analysis and prediction. An example of this is employing a three-dimensional matrix approach for treating chronic kidney;

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Android Malware Detection using Machine Learning

The authors develop a malware fingerprinting framework to cover accurate android malware detection and family attribution in this book. The;

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Android Malware Detection using Machine Learning

The authors develop a malware fingerprinting framework to cover accurate android malware detection and family attribution in this book. The;

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The Weakest Link

, cybersecurity expert Arun Vishwanath offers a new, evidence-based approach for detecting and defending against phishing—an approach that doesn’t rely on;

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Machine Learning with the Elastic Stack

as well as for classification, regression, and outlier detection. The book starts by explaining machine learning concepts in an intuitive;

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The Application of Artificial Intelligence

This book presents a unique, understandable view of machine learning using many practical examples and access to free professional software;

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The Application of Artificial Intelligence

This book presents a unique, understandable view of machine learning using many practical examples and access to free professional software;

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Understanding Machine Learning

elucidates the concepts and innovative models around prospective developments with respect to the field of machine learning. It aims to serve as a;

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Designing Machine Learning Systems with Python

machine learning * Develop techniques and strategies for dealing with large amounts of data from a variety of sources * Build models to solve;

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Machine Learning in Radiation Oncology

individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and;

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Deep Learning

Edition Style and approach This course aims to create a smooth learning path that will teach you how to effectively use deep learning with Java;

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Hands-On Machine Learning with R

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular;

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