Western-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

Jupyter Notebookiotmachine-learningdeep-learningmodel-selectiondata-preprocessingfeature-engineeringhyperparameter-tuningconcept-driftautomlintrusion-detection-systemautomated-machine-learningdata-streamspython-examplesdata-stream-processingpython-samplesiot-data-analytics
This is stars and forks stats for /Western-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics repository. As of 28 Apr, 2024 this repository has 546 stars and 102 forks.

AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics This code provides an Automated Machine Learning (AutoML) implementation for static and dynamic data analytics problems. It provides a case study of IoT anomaly detection using many ML algorithms and optimization/AutoML methods (for automating and optimizing ML algorithms). It involves the automation of all important procedures in the machine learning/data analytics pipeline, including automated data pre-processing, automated feature engineering,...
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