Customer lifetime value predictive model with Python
Datagist INC
Prepare customer data and features in Python, build BG/NBD lifetime-value models and compare XGBoost and LightGBM approaches for market-strategy decisions
Marketing focus
Define a customer-churn problem, prepare the data and build Python machine-learning models through a complete problem-to-model sequence
Eduonix Learning Solutions, Eduonix-Tech . · Udemy
Define a customer-churn problem, prepare the data and build Python machine-learning models through a complete problem-to-model sequence
Selected published requirements: “Basic knowledge of Python and ML is required to complete this course”. See the provider page for the full requirements and current tool terms
Recorded Udemy course advertised with a public course preview. Exact lesson count may be unknown. Purchase or organization-subscription terms and current availability require checking
Related tasks, tools and formats. Check the differences before choosing.
Datagist INC
Prepare customer data and features in Python, build BG/NBD lifetime-value models and compare XGBoost and LightGBM approaches for market-strategy decisions
365 Careers , Iliya Valchanov
Prepare customer data, apply hierarchical/k-means/PCA segmentation, analyze purchase data by segment and model purchase incidence, marketing mix and price response
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