gauravjgogoi Goto Github PK

codef

Official PyTorch implementation of CoDeF: Content Deformation Fields for Temporally Consistent Video Processing

dash-predictive-maintenance

Dashboard designed to demonstrate the power of Machine Learning to predict failures (Remaining Useful Life (RUL)) in wind turbines. To predict the date when equipment will completely fail (RUL), XGBoost is used and achieved RMSE error is 0.033964 days, which is highly accurate.

data-analytics-and-classification-model-for-failure-detection-of-wind-turbine

machine-failure_prediction_ensemblemethods_modeltuning

This project predicts wind turbine failure using numerous sensor data by applying classification based ML models that improves prediction by tuning model hyperparameters and addressing class imbalance through over and under sampling data. Final model is productionized using a data pipeline

metagpt

🌟 The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo

quantum_computing_course2023

Course Material for the online short course on Quantum Computing Using QSim

study-analysis-and-optimization-of-mig-welding-process-parameters-for-minimization-of-haz

sustainability-analysis-and-design-interventions-for-product-service-system

wt_fault_identification

Wind Turbine Fault Identification using Machine Learning Techniques applied to SCADA data