Marketing focus
Dedicated Telco Churn workflow: exploratory analysis, feature selection/engineering, supervised scikit-learn prediction, train/test split, confusion matrix and accuracy/precision/recall/ROC-AUC/F1, tuning and feature importance
DataCamp · DataCamp
Dedicated Telco Churn workflow: exploratory analysis, feature selection/engineering, supervised scikit-learn prediction, train/test split, confusion matrix and accuracy/precision/recall/ROC-AUC/F1, tuning and feature importance
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Related tasks, tools and formats. Check the differences before choosing.
University of Colorado Boulder
Practical workflow defines a codebook and gold labels, constructs a feature matrix, trains an elastic-net text classifier, then validates on held-out data using metrics and learning curves, Python/scikit-learn/TensorFlow are listed
O.P. Jindal Global University
Python/scikit-learn supervised workflows include marketing-engagement prediction, product recommendation, three-month customer lifetime value, neural-network churn prediction and model deployment
DataCamp
Builds click-through-rate prediction from advertising data: feature creation, classification/decision trees, cross-validation, regularization, random forests and grid-search tuning, evaluates predictions against ad-spend ROI