CyberSecurity Summary

Filtered episodes(7)

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  Artificial Intelligence: A Modern Approach (Prentice Hall Series in Artificial Intelligence)

  Published Jun 9, 2026

  Artificial Intelligence

  Define artificial intelligence through the unifying theme of intelligent agents, which are systems designed to perceive their environments and take actions that maximize their chances of success. By exploring the field’s philosophical, mathematical, and scientific foundations, the text traces how AI evolved from ancient logic and 20th-century computing into a diverse discipline. It highlights significant technical advancements since the previous edition, such as improvements in machine learning,

  machine-learning
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  Introduction to Graph Neural Networks (Synthesis Lectures on Artificial Intelligence and Machine Learning)

  Published Jun 1, 2026

  A comprehensive introduction to Graph Neural Networks (GNNs), a specialized class of deep learning models designed for non-Euclidean data structures. While traditional models like CNNs and RNNs excel at processing grids and sequences, GNNs are uniquely capable of capturing the complex relational information found in social networks, molecular structures, and traffic systems. By combining graph topology with node feature propagation and aggregation, GNNs generate high-quality representations of d

  machine-learningdeep-learning
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  Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

  Published May 30, 2026

  A comprehensive guide for building intelligent systems using popular Python frameworks like Scikit-Learn and TensorFlow. The author distinguishes between supervised, unsupervised, and reinforcement learning, while also detailing the various stages of a typical project workflow. Key concepts discussed include classification, regression, and dimensionality reduction, alongside more advanced topics like neural networks and deep learning. By focusing on a practical, hands-on approach, the text aims

  machine-learningdeep-learningtensorflow
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  Java Deep Learning Essentials

  Published May 19, 2026

  A comprehensive introduction to building artificial intelligence using the Java programming language. The text traces the historical progression of AI through three major phases, highlighting how machine learning evolved to address complex pattern recognition tasks that traditional search algorithms could not solve. It emphasizes deep learning as a revolutionary breakthrough because it allows machines to automatically identify feature quantities from raw data, overcoming a significant limitation

  machine-learningdeep-learning
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  Data Visualization and Knowledge Engineering: Spotting Data Points with Artificial Intelligence

  Published May 18, 2026

  Artificial Intelligence

  Explores how artificial intelligence is used to identify and analyze complex data points. A significant portion of the material focuses on cross-project defect prediction, a method in software engineering that utilizes external datasets to anticipate errors in new software. The authors conduct experiments using machine learning classifiers and the SMOTE algorithm to demonstrate that predicting defects across different projects is as effective as traditional within-project methods. By addressing

  machine-learning
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  Data Science and Security: Proceedings of IDSCS 2021

  Published May 15, 2026

  A scholarly volume published within the Lecture Notes in Networks and Systems series. The primary focus of the text is the intersection of data science and computational security, highlighting how these fields drive socioeconomic growth and digital reliability. Included materials feature a preface and table of contents that list various research papers covering topics like deep learning, blockchain, and privacy-preserving machine learning. Furthermore, the sources provide a detailed look at a sp

  machine-learningdeep-learning
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  Cyber Security Intelligence and Analytics (Advances in Intelligent Systems and Computing, 928)

  Published May 1, 2026

  Focuses on integrating big data analytics, machine learning, and intelligent systems to enhance threat detection and combat cybercrime. Key topics include digital forensics, incident response, and the application of computational intelligence across diverse sectors like healthcare, energy, and education. One specific paper details the use of spiral CT image processing to improve surgical accuracy and diagnostic outcomes in urology. Another article examines how data mining technology is transform

  machine-learning