The final goal of all industrial machine learning (ML) projects is to develop ML products and
rapidly bring them into production. However, it is highly challenging to automate and …

The wheel-rail interface is regarded as the most important factor for the dynamic behaviour
of a railway vehicle, affecting the safety of the service, the passenger comfort, and the life of …

Chaos engineering is a popular approach in cloud-native system resilience assessments. It
uses fault injection to test if the system is still reliable. For Kubernetes platform, which is …

Develo** and implementing the machine learning applications as quickly as feasible is
the aim of commercial machine learning (ML) initiatives. A lot of machine learning trials …

Access Control List (ACL) management in complex, distributed network environments poses
significant challenges for organizations relying on heterogeneous infrastructures. This paper …

Abstract Machine learning operations (MLOps) achieves faster model development, deliver
higher machine learning models quality, and faster deployment cycle. Unfortunately, MLOps …

This primarily aims to evaluate the ML approaches and web applications for authentication.
Using machine learning, issues can be solved, and computers can carry out tasks. It …

MLOps encompasses a collection of practices integrating machine learning into operational
activities, a recent addition to the diverse array of machine learning process models. The …

Neural Rendering, an intersection of computer graphics techniques and machine learning,
has a significant impact on the generation of hyperrealistic content. This research advocates …

الهدف من مشاريع التعلم الآلي الصناعي هو تطوير حلول تعلم الآلة في أسرع وقت ممكن ووضعها في
مرحلة الإنتاج. ومع ذلك، فإن الكثير من تجارب التعلم الآلي لا ترقى إلى مستوى متطلباتها …‎