Hi Everyone!

In this tutorial, we dive into a manufacturing dataset to explore and analyze key production metrics, including units produced, defects, downtime, and energy consumption across different machines, products, and shifts. Using Python, we simulate realistic manufacturing data, then conduct initial analysis to understand production trends. Finally, we apply a Random Forest Regressor machine learning model to predict defect counts based on other production factors, helping optimize quality control processes. This step-by-step guide is perfect for data enthusiasts and industry professionals looking to leverage data science in manufacturing.

#ManufacturingAnalytics #MachineLearning #PythonTutorial #DataScience #ManufacturingData #RandomForest #DataAnalysis #AIinManufacturing #QualityControl #ProductionOptimization #PythonCoding #DataEngineering #PredictiveMaintenance

свернуть