This repo provides source code for cross-domain machine fault diagnosis using an unsupervised domain adaptation approach (Feature Representation Alignment Networks).
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Updated
Dec 25, 2020 - Python
This repo provides source code for cross-domain machine fault diagnosis using an unsupervised domain adaptation approach (Feature Representation Alignment Networks).
An implementation of DC-Prophet by Scikit Learn (Google-cluster-data catastrophe predicting), containing data preprocessing.
The project is a machine predictive maintenance application that uses machine learning (Random Forest) to classify whether a machine will experience failure or not based on various input parameters.
Web app using the Poisson distribution to predict the number of machine failures.
Repository for Machine learning's semester project - Machine failure and failure type prediction using neural network.
Predicting Machine failure using Machine learning on a synthetic dataset of an existing milling machine consisting of 10,000 data points
Predicting failure of mechanical machines based of various sensor measurements and machine features/characteristics.
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