Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics: Theories and Applications
A

Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics: Theories and Applications

Machine learning
machine learning data mining cybersecurity big data anomaly detection intrusion detection systems cyber-physical systems
Author
Haruna Chiroma, Shafi’i M. Abdulhamid, Philippe Fournier-Viger, Nuno M. Garcia (Editors)
Publisher
Springer Nature Switzerland AG
Year
2021
Language
English
36
Rate this book

To read the book, log in / register

Preview fragment

Similar books

Architecting Data and Machine Learning Platforms: Enable Analytics and AI-Driven Innovation in the Cloud

Architecting Data and Machine Learning Platforms: Enable Analytics and AI-Driven Innovation in the Cloud

Marco Tranquillin, Valliappa Lakshmanan, Firat Tekiner

Machine Learning Algorithms Using Scikit and TensorFlow Environments

Machine Learning Algorithms Using Scikit and TensorFlow Environments

Puvvadi Baby Maruthi, Smrity Prasad, Amit Kumar Tyagi

Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Aurélien Géron

Hands-On Machine Learning with Scikit-Learn and PyTorch: Concepts, Tools, and Techniques to Build Intelligent Systems

Hands-On Machine Learning with Scikit-Learn and PyTorch: Concepts, Tools, and Techniques to Build Intelligent Systems

Aurélien Géron

Mueller J. P., Massaron L. - Machine Learning For Dummies, 2nd Edition - 2021

Mueller J. P., Massaron L. - Machine Learning For Dummies, 2nd Edition - 2021

Machine Learning for Causal Inference

Machine Learning for Causal Inference

Sheng Li, Zhixuan Chu (Editors)

Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques

Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques

Kumar Abhishek, Dr. Mounir Abdelaziz

Machine Learning Q and AI: 30 Essential Questions and Answers on Machine Learning and AI

Machine Learning Q and AI: 30 Essential Questions and Answers on Machine Learning and AI

Sebastian Raschka

Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI

Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI

Mark Ryan, Luca Massaron

Machine Learning for Engineers: Principles and Algorithms through Signal Processing and Information Theory

Machine Learning for Engineers: Principles and Algorithms through Signal Processing and Information Theory

Osvaldo Simeone