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SOH-prediction-using-NASA-Dataset

Using python and scikit-learn

Feature analysis was done on the data and relevant features were identified. Further, we fit a Support Vector Regression model to predict the State of Health(SOH) and Remaining Useful Life(RUL) of the Li-ion battery with an accuracy of 70%. Batteries B0005, B0006, B0007 and B0018 were taken as test batteries.

Future scope: Applying a deep learning model to improve the model accuracy.

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