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AndreasBraun5 / Data-Mining-in-Industrial-Processes-Evaluation-of-different-machine-learning-models-for-Prediction

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Data Mining in Industrial Processes: Evaluation of different machine learning models for product quality prediction. Evaluated model types are Random Forest, Naive Gaussian Bayes, Logistic Regression, K Nearest Neighbour and Support Vector Machine. Comparision of non time based state based approach with time series based approach. Final result in precision 99.83 %.
python data-science machine-learning data-mining sql big-data time-series nosql scikit-learn pandas artificial-intelligence data-analytics data-analysis data-preprocessing data-engineer time-series-analysis time-series-data-mining industrial-process manufacturing-process machine-learning-engineer
  • Updated May 13, 2020
udacity-azmlnd-operationalizing-machine-learning

DubWiser / udacity-azmlnd-operationalizing-machine-learning

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This project is part of the Udacity Azure ML Nanodegree. In this project, we use Azure to configure a cloud-based machine learning production model, deploy it, and consume it. We also create, publish, and consume a pipeline.
python machine-learning jupyter-notebook azure-machine-learning mlops machine-learning-engineer azure-ml-pipeline azure-ml-nanodegree mlops-workflow
  • Updated Oct 1, 2021
  • Jupyter Notebook

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