Estimating lifetime value using machine learning.
Wrapped in Kedro for deployment.
Can we build an accurate machine learning model to predict next 6 month LTV at customer level?
- Please see ./ltv_model/model/notebooks/main.ipynb
- Steps to interact with notebook:
- git clone https://github.com/jacobweiss2305/ltv_model.git
- cd ltv_model
- python -m venv venv (see provision for virtualenv installation)
- pip install -r requirements.txt
- source venv/bin/activate
- If you want to run Causal Graphical Model and Bayesian Network:
- Please see installation guide for pygraphiz: https://pygraphviz.github.io/documentation/stable/install.html
- To spin up Jupyter lab you must use kedro:
cd ./ltv_model/model/ kedro jupyter lab
- I recommend using pyenv for python version control. We are running 3.8.9. Please see provision for details (model/docs/provision.md).