main webpage W Topic Machine Learning arXiv (Cornell University) Deep Neural Networks based Meta-Learning for Network Intrusion Detection 2023 The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is difficult as network tr… Article Open Machine Learning Open Article Page

Machine Learning

Study of algorithms that improve automatically through experience Machine learning ( ML ) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalise to unseen data, and thus perform tasks without explicit instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics. Critical Symbolic Virtual Narrative Open Machine Learning Open Article Page

Exploring foci of: arXiv (Cornell University) Deep Neural Networks based Meta-Learning for Network Intrusion Detection 2023 The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is difficult as network traffic encompasses various attack types, including new and evolving ones with minor changes. The data used to construct a predictive model for computer networks has a skewed class distribution and limited representation of attack types, which differ from real n… Open Article Page

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Explore Machine Learning W Topic Machine Learning arXiv (Cornell University) Deep Neural Networks based Meta-Learning for Network Intrusion Detection 2023 The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is difficult as network tr… Article Critical Symbolic Virtual Narrative Open Machine Learning Open Article Page