Customer_lifetime_value-prediction

About

In this project I have trained a ML model to predict lifetime value of customers and divided them into 3 categories :
Gold,
Silver
and Bronze.
For better accuracy I have tune hyper parameters of multiple classification models and choose the best among them. Elbow method was used for K-means clustering. Finally tuned version of xgboost model is used with 88.9% accuracy.

Languages Used

Python

Tools Used

1. Google Colab
2. Pandas
3. Numpy
4. Scikit-learn
5. XGBoost
6. Pickle
7. RandomizedSearchCV
8. Random Forest
9. K means

Dataset Used

Online Retail Dataset from UCI Machine Repository was used. Link

Reference Resources

Kaggle Notebook