we proposed a software defect predictive development models using machine learning techniques that can enable the software to continue its projected task.

Python package to predict bugs using the complexity of code changes

AERISK(Aviation Risk Analysis System) 👉🏼 ML-based predictive maintenance for aviation safety - identifying aircraft component failures before they occur.

A bunch of example machine learning projects with real world applications

Testing rig simulation and fault prediction

Master thesis title: "Towards Event Sequence Foundation Models: exploring temporal point process transformers for power grid fault prediction" Dataset and modelling infrastructure for modelling "event streams": sequences of continuous time, multivariate events with complex internal dependencies.

A predictive maintenance model for estimating machine remaining useful life (RUL) with uncertainty. Instead of predicting a single value, the model outputs a range of plausible outcomes, enabling more informed maintenance decisions.

Company Bankruptcy Prediction with Naïve Bayes Algorithm

Predictive self-healing SDN system using Mininet, Ryu, OpenFlow 1.3, telemetry collection, and machine learning for fault prediction and proactive rerouting.