ml_engineer
CommunityBuild predictive ML models for retention.
AuthorColbyRReichenbach
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill helps data teams build, evaluate, and deploy machine learning models to predict CLV, segment customers by uplift, and optimize send times for retention campaigns.
Core Features & Use Cases
- CLV prediction models (BG/NBD) for revenue forecasting
- Uplift modeling for persuasiveness segmentation
- Send Time Optimization to maximize engagement
- End-to-end ML pipelines: training, evaluation, deployment, monitoring
- Weekly retraining with versioned artifacts and deployment hooks
Quick Start
Train a baseline CLV model on your customer transactions and generate batch predictions for a test subset.
Dependency Matrix
Required Modules
lifetimespandasscikit-learnnumpyjoblibboto3
Components
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: ml_engineer Download link: https://github.com/ColbyRReichenbach/retentionAI/archive/main.zip#ml-engineer Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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