I will build a predictive maintenance classification ml model for your dataset

I build machine learning models for predictive maintenance and classification problems using Python. This includes exploring and cleaning raw sensor or tabular data, engineering meaningful features such as rolling averages and standard deviations, handling class imbalance using techniques like class weighting, training models such as Logistic Regression and Random Forest, and evaluating them using proper metrics like ROC-AUC and PR-AUC rather than misleading accuracy scores alone. I also generate clear visualizations including ROC curves, precision-recall curves, confusion matrices, and feature importance charts to help you understand model performance. Whether you need a predictive maintenance system, a fault detection model, or a general binary classification solution for your dataset, I can build it end to end and explain the results in simple terms. I have hands-on experience applying this exact pipeline to real sensor telemetry data and adapting it to different domains.